Michael I. Jordan

CoRR, 2024

Data Acquisition via Experimental Design for Decentralized Data Markets.

[BibT_eX]

[DOI]

Charles Lu

Baihe Huang

Praneeth Vepakomma

Ramesh Raskar

CoRR, 2024

AutoEval Done Right: Using Synthetic Data for Model Evaluation.

[BibT_eX]

[DOI]

Pierre Boyeau

Nir Yosef

Anastasios Nikolas Angelopoulos

CoRR, 2024

Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference.

[BibT_eX]

[DOI]

Wei-Lin Chiang

Lianmin Zheng

Ying Sheng

CoRR, 2024

Incentivized Learning in Principal-Agent Bandit Games.

[BibT_eX]

[DOI]

CoRR, 2024

Information Elicitation in Agency Games.

[BibT_eX]

[DOI]

CoRR, 2024

On Three-Layer Data Markets.

[BibT_eX]

[DOI]

CoRR, 2024

The Limits of Price Discrimination Under Privacy Constraints.

[BibT_eX]

[DOI]

CoRR, 2024

Iterative Data Smoothing: Mitigating Reward Overfitting and Overoptimization in RLHF.

[BibT_eX]

[DOI]

CoRR, 2024

2023

Provably Efficient Reinforcement Learning with Linear Function Approximation.

[BibT_eX]

[DOI]

Math. Oper. Res., August, 2023

Learning Equilibria in Matching Markets with Bandit Feedback.

[BibT_eX]

[DOI]

J. ACM, June, 2023

Skilful nowcasting of extreme precipitation with NowcastNet.

[BibT_eX]

[DOI]

Nat., 2023

VCG Mechanism Design with Unknown Agent Values under Stochastic Bandit Feedback.

[BibT_eX]

[DOI]

Joseph E. Gonzalez

J. Mach. Learn. Res., 2023

First-Order Algorithms for Nonlinear Generalized Nash Equilibrium Problems.

[BibT_eX]

[DOI]

Manolis Zampetakis

J. Mach. Learn. Res., 2023

Can Reinforcement Learning Find Stackelberg-Nash Equilibria in General-Sum Markov Games with Myopically Rational Followers?

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2023

Towards Optimal Statistical Watermarking.

[BibT_eX]

[DOI]

CoRR, 2023

Classifier Calibration with ROC-Regularized Isotonic Regression.

[BibT_eX]

[DOI]

Eugene Berta

Emmanouil-Vasileios Vlatakis-Gkaragkounis

CoRR, 2023

A Quadratic Speedup in Finding Nash Equilibria of Quantum Zero-Sum Games.

[BibT_eX]

[DOI]

Francisca Vasconcelos

Panayotis Mertikopoulos

Georgios Piliouras

CoRR, 2023

Contract Design With Safety Inspections.

[BibT_eX]

[DOI]

Alireza Fallah

CoRR, 2023

A Specialized Semismooth Newton Method for Kernel-Based Optimal Transport.

[BibT_eX]

[DOI]

Marco Cuturi

CoRR, 2023

Adaptive, Doubly Optimal No-Regret Learning in Strongly Monotone and Exp-Concave Games with Gradient Feedback.

[BibT_eX]

[DOI]

Zhengyuan Zhou

CoRR, 2023

Conformal Decision Theory: Safe Autonomous Decisions from Imperfect Predictions.

[BibT_eX]

[DOI]

Jordan Lekeufack

Andrea Bajcsy

CoRR, 2023

A Gentle Introduction to Gradient-Based Optimization and Variational Inequalities for Machine Learning.

[BibT_eX]

[DOI]

Neha S. Wadia

Yatin Dandi

CoRR, 2023

Delegating Data Collection in Decentralized Machine Learning.

[BibT_eX]

[DOI]

Nivasini Ananthakrishnan

CoRR, 2023

Scaff-PD: Communication Efficient Fair and Robust Federated Learning.

[BibT_eX]

[DOI]

Yaodong Yu

Yi Ma

Emmanouil V. Vlatakis-Gkaragkounis

CoRR, 2023

Incentive-Theoretic Bayesian Inference for Collaborative Science.

[BibT_eX]

[DOI]

CoRR, 2023

Accelerating Inexact HyperGradient Descent for Bilevel Optimization.

[BibT_eX]

[DOI]

CoRR, 2023

Curvature-Independent Last-Iterate Convergence for Games on Riemannian Manifolds.

[BibT_eX]

[DOI]

CoRR, 2023

Provably Personalized and Robust Federated Learning.

[BibT_eX]

[DOI]

Mariel A. Werner

Lie He

Martin Jaggi

CoRR, 2023

Incentivizing High-Quality Content in Online Recommender Systems.

[BibT_eX]

[DOI]

CoRR, 2023

Evaluating and Incentivizing Diverse Data Contributions in Collaborative Learning.

[BibT_eX]

[DOI]

Baihe Huang

CoRR, 2023

Fine-Tuning Language Models with Advantage-Induced Policy Alignment.

[BibT_eX]

[DOI]

Hiteshi Sharma

Felipe Vieira Frujeri

CoRR, 2023

On Optimal Caching and Model Multiplexing for Large Model Inference.

[BibT_eX]

[DOI]

CoRR, 2023

Operationalizing Counterfactual Metrics: Incentives, Ranking, and Information Asymmetry.

[BibT_eX]

[DOI]

CoRR, 2023

Online Learning in a Creator Economy.

[BibT_eX]

[DOI]

CoRR, 2023

Finding Regularized Competitive Equilibria of Heterogeneous Agent Macroeconomic Models with Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2023

A Unifying Perspective on Multi-Calibration: Unleashing Game Dynamics for Multi-Objective Learning.

[BibT_eX]

[DOI]

Eric Zhao

CoRR, 2023

Accelerated First-Order Optimization under Nonlinear Constraints.

[BibT_eX]

[DOI]

CoRR, 2023

Prediction-Powered Inference.

[BibT_eX]

[DOI]

CoRR, 2023

Nonconvex stochastic scaled gradient descent and generalized eigenvector problems.

[BibT_eX]

[DOI]

Chris Junchi Li

Proceedings of the Uncertainty in Artificial Intelligence, 2023

The Sample Complexity of Online Contract Design.

[BibT_eX]

[DOI]

Proceedings of the 24th ACM Conference on Economics and Computation, 2023

Cilantro: Performance-Aware Resource Allocation for General Objectives via Online Feedback.

[BibT_eX]

[DOI]

Romil Bhardwaj

Proceedings of the 17th USENIX Symposium on Operating Systems Design and Implementation, 2023

Doubly-Robust Self-Training.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Towards Optimal Caching and Model Selection for Large Model Inference.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Optimal Extragradient-Based Algorithms for Stochastic Variational Inequalities with Separable Structure.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Improved Bayes Risk Can Yield Reduced Social Welfare Under Competition.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Unifying Perspective on Multi-Calibration: Game Dynamics for Multi-Objective Learning.

[BibT_eX]

[DOI]

Eric Zhao

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Class-Conditional Conformal Prediction with Many Classes.

[BibT_eX]

[DOI]

Tiffany Ding

Anastasios Angelopoulos

Ryan J. Tibshirani

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

On Learning Necessary and Sufficient Causal Graphs.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

KDD-2023 Workshop on Decision Intelligence and Analytics for Online Marketplaces.

[BibT_eX]

[DOI]

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Principled Reinforcement Learning with Human Feedback from Pairwise or K-wise Comparisons.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Online Learning in Stackelberg Games with an Omniscient Follower.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Federated Conformal Predictors for Distributed Uncertainty Quantification.

[BibT_eX]

[DOI]

Charles Lu

Yaodong Yu

Ramesh Raskar

Proceedings of the International Conference on Machine Learning, 2023

Nesterov Meets Optimism: Rate-Optimal Separable Minimax Optimization.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Solving Constrained Variational Inequalities via a First-order Interior Point-based Method.

[BibT_eX]

[DOI]

Tong Yang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Modeling content creator incentives on algorithm-curated platforms.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

A General Framework for Sample-Efficient Function Approximation in Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Neural Dependencies Emerging from Learning Massive Categories.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Recommendation Systems with Distribution-Free Reliability Guarantees.

[BibT_eX]

[DOI]

Proceedings of the Conformal and Probabilistic Prediction with Applications, 2023

Deterministic Nonsmooth Nonconvex Optimization.

[BibT_eX]

[DOI]

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

An Instance-Dependent Analysis for the Cooperative Multi-Player Multi-Armed Bandit.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Algorithmic Learning Theory, 2023

Byzantine-Robust Federated Learning with Optimal Statistical Rates.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Finding Regularized Competitive Equilibria of Heterogeneous Agent Macroeconomic Models via Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

A Statistical Analysis of Polyak-Ruppert Averaged Q-Learning.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Competition, Alignment, and Equilibria in Digital Marketplaces.

[BibT_eX]

[DOI]

Meena Jagadeesan

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Multi-Source Causal Inference Using Control Variates under Outcome Selection Bias.

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2022

Adaptivity of Stochastic Gradient Methods for Nonconvex Optimization.

[BibT_eX]

[DOI]

SIAM J. Math. Data Sci., 2022

KDD 2022 Workshop on Decision Intelligence and Analytics for Online Marketplaces: Jobs, Ridesharing, Retail, and Beyond.

[BibT_eX]

[DOI]

SIGKDD Explor., 2022

Understanding the acceleration phenomenon via high-resolution differential equations.

[BibT_eX]

[DOI]

Math. Program., 2022

A control-theoretic perspective on optimal high-order optimization.

[BibT_eX]

[DOI]

Math. Program., 2022

SOUL: An Energy-Efficient Unsupervised Online Learning Seizure Detection Classifier.

[BibT_eX]

[DOI]

Adelson Chua

Rikky Muller

IEEE J. Solid State Circuits, 2022

Ranking and Tuning Pre-trained Models: A New Paradigm for Exploiting Model Hubs.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2022

On Constraints in First-Order Optimization: A View from Non-Smooth Dynamical Systems.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2022

Active Learning for Nonlinear System Identification with Guarantees.

[BibT_eX]

[DOI]

Horia Mania

J. Mach. Learn. Res., 2022

On the Efficiency of Entropic Regularized Algorithms for Optimal Transport.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2022

On the Complexity of Approximating Multimarginal Optimal Transport.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2022

Convergence Rates for Gaussian Mixtures of Experts.

[BibT_eX]

[DOI]

Chiao-Yu Yang

J. Mach. Learn. Res., 2022

Incentive-Aware Recommender Systems in Two-Sided Markets.

[BibT_eX]

[DOI]

Yuan Qi

CoRR, 2022

Nesterov Meets Optimism: Rate-Optimal Optimistic-Gradient-Based Method for Stochastic Bilinearly-Coupled Minimax Optimization.

[BibT_eX]

[DOI]

CoRR, 2022

Revisiting the ACVI Method for Constrained Variational Inequalities.

[BibT_eX]

[DOI]

CoRR, 2022

Explicit Second-Order Min-Max Optimization Methods with Optimal Convergence Guarantee.

[BibT_eX]

[DOI]

Panayotis Mertikopoulos

CoRR, 2022

A Reinforcement Learning Approach in Multi-Phase Second-Price Auction Design.

[BibT_eX]

[DOI]

CoRR, 2022

A General Framework for Sample-Efficient Function Approximation in Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2022

On the Complexity of Deterministic Nonsmooth and Nonconvex Optimization.

[BibT_eX]

[DOI]

Manolis Zampetakis

CoRR, 2022

Valid Inference after Causal Discovery.

[BibT_eX]

[DOI]

CoRR, 2022

Learning Two-Player Mixture Markov Games: Kernel Function Approximation and Correlated Equilibrium.

[BibT_eX]

[DOI]

CoRR, 2022

Continuous-time Analysis for Variational Inequalities: An Overview and Desiderata.

[BibT_eX]

[DOI]

Ya-Ping Hsieh

CoRR, 2022

Mechanisms that Incentivize Data Sharing in Federated Learning.

[BibT_eX]

[DOI]

CoRR, 2022

Breaking Feedback Loops in Recommender Systems with Causal Inference.

[BibT_eX]

[DOI]

Karl Krauth

Yixin Wang

CoRR, 2022

NumS: Scalable Array Programming for the Cloud.

[BibT_eX]

[DOI]

CoRR, 2022

Solving Constrained Variational Inequalities via an Interior Point Method.

[BibT_eX]

[DOI]

Tong Yang

CoRR, 2022

Optimal Extragradient-Based Bilinearly-Coupled Saddle-Point Optimization.

[BibT_eX]

[DOI]

CoRR, 2022

A Continuous-Time Perspective on Monotone Equation Problems.

[BibT_eX]

[DOI]

CoRR, 2022

Byzantine-Robust Federated Learning with Optimal Statistical Rates and Privacy Guarantees.

[BibT_eX]

[DOI]

CoRR, 2022

The Sky Above The Clouds.

[BibT_eX]

[DOI]

Anthony D. Joseph

Michael W. Mahoney

Aditya G. Parameswaran

CoRR, 2022

Principal-Agent Hypothesis Testing.

[BibT_eX]

[DOI]

CoRR, 2022

Perseus: A Simple High-Order Regularization Method for Variational Inequalities.

[BibT_eX]

[DOI]

CoRR, 2022

Geometric Methods for Sampling, Optimisation, Inference and Adaptive Agents.

[BibT_eX]

[DOI]

Grigorios A. Pavliotis

CoRR, 2022

Learning Dynamic Mechanisms in Unknown Environments: A Reinforcement Learning Approach.

[BibT_eX]

[DOI]

CoRR, 2022

Improving Generalization via Uncertainty Driven Perturbations.

[BibT_eX]

[DOI]

CoRR, 2022

Transferred Q-learning.

[BibT_eX]

[DOI]

Elynn Y. Chen

Sai Li

CoRR, 2022

Conformal prediction for the design problem.

[BibT_eX]

[DOI]

Clara Fannjiang

Jennifer Listgarten

CoRR, 2022

Robust Estimation for Nonparametric Families via Generative Adversarial Networks.

[BibT_eX]

[DOI]

CoRR, 2022

Reinforcement Learning with Heterogeneous Data: Estimation and Inference.

[BibT_eX]

[DOI]

Elynn Y. Chen

Rui Song

CoRR, 2022

Online Active Learning with Dynamic Marginal Gain Thresholding.

[BibT_eX]

[DOI]

Mariel A. Werner

Anastasios Angelopoulos

CoRR, 2022

Instance-Dependent Confidence and Early Stopping for Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2022

Optimal variance-reduced stochastic approximation in Banach spaces.

[BibT_eX]

[DOI]

CoRR, 2022

Sequential Information Design: Markov Persuasion Process and Its Efficient Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the EC '22: The 23rd ACM Conference on Economics and Computation, Boulder, CO, USA, July 11, 2022

Identifying Systematic Variation at the Single-Cell Level by Leveraging Low-Resolution Population-Level Data.

[BibT_eX]

[DOI]

Elior Rahmani

Nir Yosef

Proceedings of the Research in Computational Molecular Biology, 2022

Robust Calibration with Multi-domain Temperature Scaling.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

TCT: Convexifying Federated Learning using Bootstrapped Neural Tangent Kernels.

[BibT_eX]

[DOI]

Yaodong Yu

Alexander Wei

Yi Ma

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Learn to Match with No Regret: Reinforcement Learning in Markov Matching Markets.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Gradient-Free Methods for Deterministic and Stochastic Nonsmooth Nonconvex Optimization.

[BibT_eX]

[DOI]

Zeyu Zheng

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Learning Two-Player Markov Games: Neural Function Approximation and Correlated Equilibrium.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Empirical Gateaux Derivatives for Causal Inference.

[BibT_eX]

[DOI]

Yixin Wang

Angela Zhou

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

First-Order Algorithms for Min-Max Optimization in Geodesic Metric Spaces.

[BibT_eX]

[DOI]

Emmanouil V. Vlatakis-Gkaragkounis

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

On-Demand Sampling: Learning Optimally from Multiple Distributions.

[BibT_eX]

[DOI]

Eric Zhao

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Off-Policy Evaluation with Policy-Dependent Optimization Response.

[BibT_eX]

[DOI]

Angela Zhou

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Rank Diminishing in Deep Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

The 5th Artificial Intelligence of Things (AIoT) Workshop.

[BibT_eX]

[DOI]

Vijaykrishnan Narayanan

Mani B. Srivastava

Victor Bahl

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Decision Intelligence and Analytics for Online Marketplaces: Jobs, Ridesharing, Retail and Beyond.

[BibT_eX]

[DOI]

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Robust Estimation for Non-parametric Families via Generative Adversarial Networks.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Information Theory, 2022

Welfare Maximization in Competitive Equilibrium: Reinforcement Learning for Markov Exchange Economy.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Online Nonsubmodular Minimization with Delayed Costs: From Full Information to Bandit Feedback.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

No-Regret Learning in Partially-Informed Auctions.

[BibT_eX]

[DOI]

Ellen Vitercik

Proceedings of the International Conference on Machine Learning, 2022

Image-to-Image Regression with Distribution-Free Uncertainty Quantification and Applications in Imaging.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

ROOT-SGD: Sharp Nonasymptotics and Asymptotic Efficiency in a Single Algorithm.

[BibT_eX]

[DOI]

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

Optimal Mean Estimation without a Variance.

[BibT_eX]

[DOI]

Yeshwanth Cherapanamjeri

Nilesh Tripuraneni

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

Partial Identification with Noisy Covariates: A Robust Optimization Approach.

[BibT_eX]

[DOI]

Proceedings of the 1st Conference on Causal Learning and Reasoning, 2022

Fast Distributionally Robust Learning with Variance-Reduced Min-Max Optimization.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

On the Convergence of Stochastic Extragradient for Bilinear Games using Restarted Iteration Averaging.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

On Structured Filtering-Clustering: Global Error Bound and Optimal First-Order Algorithms.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Learning Competitive Equilibria in Exchange Economies with Bandit Feedback.

[BibT_eX]

[DOI]

Joseph Gonzalez

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Is Temporal Difference Learning Optimal? An Instance-Dependent Analysis.

[BibT_eX]

[DOI]

SIAM J. Math. Data Sci., 2021

Generalized Momentum-Based Methods: A Hamiltonian Perspective.

[BibT_eX]

[DOI]

Jelena Diakonikolas

SIAM J. Optim., 2021

Asynchronous Online Testing of Multiple Hypotheses.

[BibT_eX]

[DOI]

Tijana Zrnic

Aaditya Ramdas

J. Mach. Learn. Res., 2021

A Lyapunov Analysis of Accelerated Methods in Optimization.

[BibT_eX]

[DOI]

Ashia C. Wilson

Ben Recht

J. Mach. Learn. Res., 2021

Optimization with Momentum: Dynamical, Control-Theoretic, and Symplectic Perspectives.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2021

High-Order Langevin Diffusion Yields an Accelerated MCMC Algorithm.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2021

Bandit Learning in Decentralized Matching Markets.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2021

Learning Strategies in Decentralized Matching Markets under Uncertain Preferences.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2021

On Nonconvex Optimization for Machine Learning: Gradients, Stochasticity, and Saddle Points.

[BibT_eX]

[DOI]

J. ACM, 2021

Distribution-free, Risk-controlling Prediction Sets.

[BibT_eX]

[DOI]

Anastasios Angelopoulos

J. ACM, 2021

Polyak-Ruppert Averaged Q-Leaning is Statistically Efficient.

[BibT_eX]

[DOI]

CoRR, 2021

Last-Iterate Convergence of Saddle Point Optimizers via High-Resolution Differential Equations.

[BibT_eX]

[DOI]

Manolis Zampetakis

CoRR, 2021

Can Reinforcement Learning Find Stackelberg-Nash Equilibria in General-Sum Markov Games with Myopic Followers?

[BibT_eX]

[DOI]

CoRR, 2021

ElegantRL-Podracer: Scalable and Elastic Library for Cloud-Native Deep Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2021

On Monotone Inclusions, Acceleration and Closed-Loop Control.

[BibT_eX]

[DOI]

CoRR, 2021

Cluster-and-Conquer: A Framework For Time-Series Forecasting.

[BibT_eX]

[DOI]

CoRR, 2021

Ranking and Tuning Pre-trained Models: A New Paradigm of Exploiting Model Hubs.

[BibT_eX]

[DOI]

CoRR, 2021

On the Self-Penalization Phenomenon in Feature Selection.

[BibT_eX]

[DOI]

Keli Liu

Feng Ruan

CoRR, 2021

Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control.

[BibT_eX]

[DOI]

CoRR, 2021

Desiderata for Representation Learning: A Causal Perspective.

[BibT_eX]

[DOI]

Yixin Wang

CoRR, 2021

Data Sharing Markets.

[BibT_eX]

[DOI]

Mohammad Rasouli

CoRR, 2021

On the Convergence of Stochastic Extragradient for Bilinear Games with Restarted Iteration Averaging.

[BibT_eX]

[DOI]

CoRR, 2021

Variational Refinement for Importance Sampling Using the Forward Kullback-Leibler Divergence.

[BibT_eX]

[DOI]

CoRR, 2021

Instance-optimality in optimal value estimation: Adaptivity via variance-reduced Q-learning.

[BibT_eX]

[DOI]

CoRR, 2021

Online Learning of Competitive Equilibria in Exchange Economies.

[BibT_eX]

[DOI]

Joseph E. Gonzalez

CoRR, 2021

PAC Best Arm Identification Under a Deadline.

[BibT_eX]

[DOI]

Brijen Thananjeyan

CoRR, 2021

Parallelizing Contextual Linear Bandits.

[BibT_eX]

[DOI]

CoRR, 2021

Multi-Source Causal Inference Using Control Variates.

[BibT_eX]

[DOI]

CoRR, 2021

Interleaving Computational and Inferential Thinking: Data Science for Undergraduates at Berkeley.

[BibT_eX]

[DOI]

Ani Adhikari

John DeNero

CoRR, 2021

Multi-Stage Decentralized Matching Markets: Uncertain Preferences and Strategic Behaviors.

[BibT_eX]

[DOI]

CoRR, 2021

Private Prediction Sets.

[BibT_eX]

[DOI]

Tijana Zrnic

CoRR, 2021

A 1.5nJ/cls Unsupervised Online Learning Classifier for Seizure Detection.

[BibT_eX]

[DOI]

Adelson Chua

Rikky Muller

Proceedings of the 2021 Symposium on VLSI Circuits, Kyoto, Japan, June 13-19, 2021, 2021

Variational refinement for importance sampling using the forward Kullback-Leibler divergence.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Who Leads and Who Follows in Strategic Classification?

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Wasserstein Flow Meets Replicator Dynamics: A Mean-Field Analysis of Representation Learning in Actor-Critic.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Tactical Optimism and Pessimism for Deep Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Test-time Collective Prediction.

[BibT_eX]

[DOI]

Celestine Mendler-Dünner

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Learning Equilibria in Matching Markets from Bandit Feedback.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

On Component Interactions in Two-Stage Recommender Systems.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Robust Learning of Optimal Auctions.

[BibT_eX]

[DOI]

Emmanouil Zampetakis

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Learning in Multi-Stage Decentralized Matching Markets.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

On the Theory of Reinforcement Learning with Once-per-Episode Feedback.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

The 4th Artificial Intelligence of Things (AIoT) Workshop.

[BibT_eX]

[DOI]

Vijaykrishnan Narayanan

Mani Srivastava

Victor Bahl

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Provable Meta-Learning of Linear Representations.

[BibT_eX]

[DOI]

Nilesh Tripuraneni

Proceedings of the 38th International Conference on Machine Learning, 2021

Resource Allocation in Multi-armed Bandit Exploration: Overcoming Sublinear Scaling with Adaptive Parallelism.

[BibT_eX]

[DOI]

Brijen Thananjeyan

Anastasios Nikolas Angelopoulos

Proceedings of the 38th International Conference on Machine Learning, 2021

Representation Matters: Assessing the Importance of Subgroup Allocations in Training Data.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Uncertainty Sets for Image Classifiers using Conformal Prediction.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Learning Representations, 2021

The Stereotyping Problem in Collaboratively Filtered Recommender Systems.

[BibT_eX]

[DOI]

Proceedings of the EAAMO 2021: ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization, Virtual Event, USA, October 5, 2021

Stochastic Approximation for Online Tensorial Independent Component Analysis.

[BibT_eX]

[DOI]

Chris Junchi Li

Proceedings of the Conference on Learning Theory, 2021

Elastic Hyperparameter Tuning on the Cloud.

[BibT_eX]

[DOI]

Lisa Dunlap

Proceedings of the SoCC '21: ACM Symposium on Cloud Computing, 2021

On the Stability of Nonlinear Receding Horizon Control: A Geometric Perspective.

[BibT_eX]

[DOI]

Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

A Variational Inequality Approach to Bayesian Regression Games.

[BibT_eX]

[DOI]

Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

On Projection Robust Optimal Transport: Sample Complexity and Model Misspecification.

[BibT_eX]

[DOI]

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Efficient Methods for Structured Nonconvex-Nonconcave Min-Max Optimization.

[BibT_eX]

[DOI]

Jelena Diakonikolas

Constantinos Daskalakis

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Robustness Guarantees for Mode Estimation with an Application to Bandits.

[BibT_eX]

[DOI]

Heinrich Jiang

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Learning from eXtreme Bandit Feedback.

[BibT_eX]

[DOI]

Romain Lopez

Inderjit S. Dhillon

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

On the Adaptivity of Stochastic Gradient-Based Optimization.

[BibT_eX]

[DOI]

SIAM J. Optim., 2020

Greedy Attack and Gumbel Attack: Generating Adversarial Examples for Discrete Data.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2020

Online Learning Demands in Max-min Fairness.

[BibT_eX]

[DOI]

CoRR, 2020

Do Offline Metrics Predict Online Performance in Recommender Systems?

[BibT_eX]

[DOI]

CoRR, 2020

Bridging Exploration and General Function Approximation in Reinforcement Learning: Provably Efficient Kernel and Neural Value Iterations.

[BibT_eX]

[DOI]

CoRR, 2020

Resource Allocation in Multi-armed Bandit Exploration: Overcoming Nonlinear Scaling with Adaptive Parallelism.

[BibT_eX]

[DOI]

Brijen Thananjeyan

CoRR, 2020

Exploration in two-stage recommender systems.

[BibT_eX]

[DOI]

CoRR, 2020

On Localized Discrepancy for Domain Adaptation.

[BibT_eX]

[DOI]

CoRR, 2020

Optimal Robust Linear Regression in Nearly Linear Time.

[BibT_eX]

[DOI]

Yeshwanth Cherapanamjeri

CoRR, 2020

Finding Equilibrium in Multi-Agent Games with Payoff Uncertainty.

[BibT_eX]

[DOI]

CoRR, 2020

Manifold Learning via Manifold Deflation.

[BibT_eX]

[DOI]

Daniel Ting

CoRR, 2020

Instability, Computational Efficiency and Statistical Accuracy.

[BibT_eX]

[DOI]

CoRR, 2020

Lower bounds in multiple testing: A framework based on derandomized proxies.

[BibT_eX]

[DOI]

Max Rabinovich

CoRR, 2020

Mechanism Design with Bandit Feedback.

[BibT_eX]

[DOI]

Joseph E. Gonzalez

CoRR, 2020

On Learning Rates and Schrödinger Operators.

[BibT_eX]

[DOI]

Bin Shi

Weijie J. Su

CoRR, 2020

On Thompson Sampling with Langevin Algorithms.

[BibT_eX]

[DOI]

CoRR, 2020

Revisiting Fixed Support Wasserstein Barycenter: Computational Hardness and Efficient Algorithms.

[BibT_eX]

[DOI]

CoRR, 2020

HopSkipJumpAttack: A Query-Efficient Decision-Based Attack.

[BibT_eX]

[DOI]

Jianbo Chen

Proceedings of the 2020 IEEE Symposium on Security and Privacy, 2020

Provably Efficient Reinforcement Learning with Kernel and Neural Function Approximations.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Transferable Calibration with Lower Bias and Variance in Domain Adaptation.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Robust Optimization for Fairness with Noisy Protected Groups.

[BibT_eX]

[DOI]

Serena Lutong Wang

Harikrishna Narasimhan

Andrew Cotter

Maya R. Gupta

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

On the Theory of Transfer Learning: The Importance of Task Diversity.

[BibT_eX]

[DOI]

Nilesh Tripuraneni

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Decision-Making with Auto-Encoding Variational Bayes.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Fixed-Support Wasserstein Barycenters: Computational Hardness and Fast Algorithm.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Projection Robust Wasserstein Distance and Riemannian Optimization.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning to Score Behaviors for Guided Policy Optimization.

[BibT_eX]

[DOI]

Jack Parker-Holder

Yunhao Tang

Krzysztof Choromanski

Anna Choromanska

Proceedings of the 37th International Conference on Machine Learning, 2020

Continuous-time Lower Bounds for Gradient-based Algorithms.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

On Approximate Thompson Sampling with Langevin Algorithms.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

Finite-Time Last-Iterate Convergence for Multi-Agent Learning in Games.

[BibT_eX]

[DOI]

Zhengyuan Zhou

Panayotis Mertikopoulos

Proceedings of the 37th International Conference on Machine Learning, 2020

On Gradient Descent Ascent for Nonconvex-Concave Minimax Problems.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

Accelerated Message Passing for Entropy-Regularized MAP Inference.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

What is Local Optimality in Nonconvex-Nonconcave Minimax Optimization?

[BibT_eX]

[DOI]

Praneeth Netrapalli

Proceedings of the 37th International Conference on Machine Learning, 2020

Stochastic Gradient and Langevin Processes.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

Variance Reduction With Sparse Gradients.

[BibT_eX]

[DOI]

Melih Elibol

Proceedings of the 8th International Conference on Learning Representations, 2020

Unsupervised Online Learning for Long-Term High Sensitivity Seizure Detection.

[BibT_eX]

[DOI]

Adelson Chua

Rikky Muller

Proceedings of the 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2020

On Linear Stochastic Approximation: Fine-grained Polyak-Ruppert and Non-Asymptotic Concentration.

[BibT_eX]

[DOI]

Proceedings of the Conference on Learning Theory, 2020

Near-Optimal Algorithms for Minimax Optimization.

[BibT_eX]

[DOI]

Proceedings of the Conference on Learning Theory, 2020

High Confidence Sets for Trajectories of Stochastic Time-Varying Nonlinear Systems.

[BibT_eX]

[DOI]

Proceedings of the 59th IEEE Conference on Decision and Control, 2020

Policy-Gradient Algorithms Have No Guarantees of Convergence in Linear Quadratic Games.

[BibT_eX]

[DOI]

Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

Improved Sample Complexity for Stochastic Compositional Variance Reduced Gradient.

[BibT_eX]

[DOI]

Proceedings of the 2020 American Control Conference, 2020

The Power of Batching in Multiple Hypothesis Testing.

[BibT_eX]

[DOI]

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Post-Estimation Smoothing: A Simple Baseline for Learning with Side Information.

[BibT_eX]

[DOI]

Esther Rolf

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Competing Bandits in Matching Markets.

[BibT_eX]

[DOI]

Lydia T. Liu

Horia Mania

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Convergence Rates of Smooth Message Passing with Rounding in Entropy-Regularized MAP Inference.

[BibT_eX]

[DOI]

Jonathan N. Lee

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Fast Algorithms for Computational Optimal Transport and Wasserstein Barycenter.

[BibT_eX]

[DOI]

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Sharp Analysis of Expectation-Maximization for Weakly Identifiable Models.

[BibT_eX]

[DOI]

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Langevin Monte Carlo without smoothness.

[BibT_eX]

[DOI]

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

ML-LOO: Detecting Adversarial Examples with Feature Attribution.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Cost-Effective Incentive Allocation via Structured Counterfactual Inference.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

LS-Tree: Model Interpretation When the Data Are Linguistic.

[BibT_eX]

[DOI]

Jianbo Chen

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Decoding From Pooled Data: Phase Transitions of Message Passing.

[BibT_eX]

[DOI]

IEEE Trans. Inf. Theory, 2019

Decoding from Pooled Data: Sharp Information-Theoretic Bounds.

[BibT_eX]

[DOI]

SIAM J. Math. Data Sci., 2019

Transferable Representation Learning with Deep Adaptation Networks.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2019

First-order methods almost always avoid strict saddle points.

[BibT_eX]

[DOI]

Math. Program., 2019

Sampling for Bayesian Mixture Models: MCMC with Polynomial-Time Mixing.

[BibT_eX]

[DOI]

CoRR, 2019

Towards Understanding the Transferability of Deep Representations.

[BibT_eX]

[DOI]

CoRR, 2019

Learning Stages: Phenomenon, Root Cause, Mechanism Hypothesis, and Implications.

[BibT_eX]

[DOI]

CoRR, 2019

A Higher-Order Swiss Army Infinitesimal Jackknife.

[BibT_eX]

[DOI]

CoRR, 2019

Bayesian Robustness: A Nonasymptotic Viewpoint.

[BibT_eX]

[DOI]

CoRR, 2019

Policy-Gradient Algorithms Have No Guarantees of Convergence in Continuous Action and State Multi-Agent Settings.

[BibT_eX]

[DOI]

CoRR, 2019

Quantitative W1 Convergence of Langevin-Like Stochastic Processes with Non-Convex Potential State-Dependent Noise.

[BibT_eX]

[DOI]

CoRR, 2019

Approximate Sherali-Adams Relaxations for MAP Inference via Entropy Regularization.

[BibT_eX]

[DOI]

Jonathan N. Lee

CoRR, 2019

Wasserstein Reinforcement Learning.

[BibT_eX]

[DOI]

Krzysztof Choromanski

CoRR, 2019

On the Acceleration of the Sinkhorn and Greenkhorn Algorithms for Optimal Transport.

[BibT_eX]

[DOI]

CoRR, 2019

Posterior Distribution for the Number of Clusters in Dirichlet Process Mixture Models.

[BibT_eX]

[DOI]

Chiao-Yu Yang

CoRR, 2019

Accelerated Primal-Dual Coordinate Descent for Computational Optimal Transport.

[BibT_eX]

[DOI]

CoRR, 2019

A joint model of unpaired data from scRNA-seq and spatial transcriptomics for imputing missing gene expression measurements.

[BibT_eX]

[DOI]

CoRR, 2019

Global Error Bounds and Linear Convergence for Gradient-Based Algorithms for Trend Filtering and 𝓁1-Convex Clustering.

[BibT_eX]

[DOI]

CoRR, 2019

SysML: The New Frontier of Machine Learning Systems.

[BibT_eX]

[DOI]

Alexandros G. Dimakis

Anastasios Kyrillidis

Shivaram Venkataraman

CoRR, 2019

Boundary Attack++: Query-Efficient Decision-Based Adversarial Attack.

[BibT_eX]

[DOI]

Jianbo Chen

CoRR, 2019

Stochastic Gradient Descent Escapes Saddle Points Efficiently.

[BibT_eX]

[DOI]

CoRR, 2019

A Short Note on Concentration Inequalities for Random Vectors with SubGaussian Norm.

[BibT_eX]

[DOI]

CoRR, 2019

Is There an Analog of Nesterov Acceleration for MCMC?

[BibT_eX]

[DOI]

CoRR, 2019

Quantitative Central Limit Theorems for Discrete Stochastic Processes.

[BibT_eX]

[DOI]

Xiang Cheng

CoRR, 2019

Minmax Optimization: Stable Limit Points of Gradient Descent Ascent are Locally Optimal.

[BibT_eX]

[DOI]

Praneeth Netrapalli

CoRR, 2019

Challenges with EM in application to weakly identifiable mixture models.

[BibT_eX]

[DOI]

CoRR, 2019

On Finding Local Nash Equilibria (and Only Local Nash Equilibria) in Zero-Sum Games.

[BibT_eX]

[DOI]

Eric Mazumdar

S. Shankar Sastry

CoRR, 2019

Transferable Normalization: Towards Improving Transferability of Deep Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Acceleration via Symplectic Discretization of High-Resolution Differential Equations.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Theoretically Principled Trade-off between Robustness and Accuracy.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

Towards Accurate Model Selection in Deep Unsupervised Domain Adaptation.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

A Dynamical Systems Perspective on Nesterov Acceleration.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

Rao-Blackwellized Stochastic Gradients for Discrete Distributions.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

Transferable Adversarial Training: A General Approach to Adapting Deep Classifiers.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

On Efficient Optimal Transport: An Analysis of Greedy and Accelerated Mirror Descent Algorithms.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

Bridging Theory and Algorithm for Domain Adaptation.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

L-Shapley and C-Shapley: Efficient Model Interpretation for Structured Data.

[BibT_eX]

[DOI]

Proceedings of the 7th International Conference on Learning Representations, 2019

Universal Domain Adaptation.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Probabilistic Multilevel Clustering via Composite Transportation Distance.

[BibT_eX]

[DOI]

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

A Swiss Army Infinitesimal Jackknife.

[BibT_eX]

[DOI]

William T. Stephenson

Runjing Liu

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Covariances, Robustness, and Variational Bayes.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2018

Sampling Can Be Faster Than Optimization.

[BibT_eX]

[DOI]

CoRR, 2018

Gen-Oja: A Simple and Efficient Algorithm for Streaming Generalized Eigenvector Computation.

[BibT_eX]

[DOI]

CoRR, 2018

Neural Rendering Model: Joint Generation and Prediction for Semi-Supervised Learning.

[BibT_eX]

[DOI]

CoRR, 2018

A Deep Generative Model for Semi-Supervised Classification with Noisy Labels.

[BibT_eX]

[DOI]

CoRR, 2018

Improved Oracle Complexity for Stochastic Compositional Variance Reduced Gradient.

[BibT_eX]

[DOI]

CoRR, 2018

Sharp Convergence Rates for Langevin Dynamics in the Nonconvex Setting.

[BibT_eX]

[DOI]

CoRR, 2018

Minimizing Nonconvex Population Risk from Rough Empirical Risk.

[BibT_eX]

[DOI]

CoRR, 2018

Model-Based Value Estimation for Efficient Model-Free Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2018

Ray: A Distributed Framework for Emerging AI Applications.

[BibT_eX]

[DOI]

Proceedings of the 13th USENIX Symposium on Operating Systems Design and Implementation, 2018

Stochastic Cubic Regularization for Fast Nonconvex Optimization.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Information Constraints on Auto-Encoding Variational Bayes.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Conditional Adversarial Domain Adaptation.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Generalized Zero-Shot Learning with Deep Calibration Network.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

On the Local Minima of the Empirical Risk.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Is Q-Learning Provably Efficient?

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Theoretical guarantees for EM under misspecified Gaussian mixture models.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Gen-Oja: Simple & Efficient Algorithm for Streaming Generalized Eigenvector Computation.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

SAFFRON: an Adaptive Algorithm for Online Control of the False Discovery Rate.

[BibT_eX]

[DOI]

Proceedings of the 35th International Conference on Machine Learning, 2018

RLlib: Abstractions for Distributed Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the 35th International Conference on Machine Learning, 2018

Learning to Explain: An Information-Theoretic Perspective on Model Interpretation.

[BibT_eX]

[DOI]

Proceedings of the 35th International Conference on Machine Learning, 2018

On the Theory of Variance Reduction for Stochastic Gradient Monte Carlo.

[BibT_eX]

[DOI]

Proceedings of the 35th International Conference on Machine Learning, 2018

Partial Transfer Learning With Selective Adversarial Networks.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

Averaging Stochastic Gradient Descent on Riemannian Manifolds.

[BibT_eX]

[DOI]

Proceedings of the Conference On Learning Theory, 2018

Learning Without Mixing: Towards A Sharp Analysis of Linear System Identification.

[BibT_eX]

[DOI]

Proceedings of the Conference On Learning Theory, 2018

Accelerated Gradient Descent Escapes Saddle Points Faster than Gradient Descent.

[BibT_eX]

[DOI]

Praneeth Netrapalli

Proceedings of the Conference On Learning Theory, 2018

Underdamped Langevin MCMC: A non-asymptotic analysis.

[BibT_eX]

[DOI]

Proceedings of the Conference On Learning Theory, 2018

Detection limits in the high-dimensional spiked rectangular model.

[BibT_eX]

[DOI]

Ahmed El Alaoui

Proceedings of the Conference On Learning Theory, 2018

Machine learning: trends, perspectives and challenges.

[BibT_eX]

[DOI]

Proceedings of ACM Turing Celebration Conference - China, 2018

2017

A Marked Poisson Process Driven Latent Shape Model for 3D Segmentation of Reflectance Confocal Microscopy Image Stacks of Human Skin.

[BibT_eX]

[DOI]

IEEE Trans. Image Process., 2017

Perturbed Iterate Analysis for Asynchronous Stochastic Optimization.

[BibT_eX]

[DOI]

Horia Mania

Xinghao Pan

Kannan Ramchandran

SIAM J. Optim., 2017

Distributed optimization with arbitrary local solvers.

[BibT_eX]

[DOI]

Optim. Methods Softw., 2017

CoCoA: A General Framework for Communication-Efficient Distributed Optimization.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2017

Saturating Splines and Feature Selection.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2017

Ray: A Distributed Framework for Emerging AI Applications.

[BibT_eX]

[DOI]

CoRR, 2017

A Berkeley View of Systems Challenges for AI.

[BibT_eX]

[DOI]

CoRR, 2017

First-order Methods Almost Always Avoid Saddle Points.

[BibT_eX]

[DOI]

CoRR, 2017

Finite Size Corrections and Likelihood Ratio Fluctuations in the Spiked Wigner Model.

[BibT_eX]

[DOI]

Ahmed El Alaoui

Florent Krzakala

CoRR, 2017

DAGGER: A sequential algorithm for FDR control on DAGs.

[BibT_eX]

[DOI]

CoRR, 2017

A deep generative model for gene expression profiles from single-cell RNA sequencing.

[BibT_eX]

[DOI]

CoRR, 2017

Real-Time Machine Learning: The Missing Pieces.

[BibT_eX]

[DOI]

Johann Schleier-Smith

Richard Liaw

CoRR, 2017

Domain Adaptation with Randomized Multilinear Adversarial Networks.

[BibT_eX]

[DOI]

CoRR, 2017

Nonconvex Finite-Sum Optimization Via SCSG Methods.

[BibT_eX]

[DOI]

CoRR, 2017

On Gradient-Based Optimization: Accelerated, Distributed, Asynchronous and Stochastic.

[BibT_eX]

[DOI]

Proceedings of the 2017 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems, Urbana-Champaign, IL, USA, June 05, 2017

Fast Black-box Variational Inference through Stochastic Trust-Region Optimization.

[BibT_eX]

[DOI]

Jeffrey Regier

Jon McAuliffe

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Online control of the false discovery rate with decaying memory.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Non-convex Finite-Sum Optimization Via SCSG Methods.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Gradient Descent Can Take Exponential Time to Escape Saddle Points.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Kernel Feature Selection via Conditional Covariance Minimization.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Breaking Locality Accelerates Block Gauss-Seidel.

[BibT_eX]

[DOI]

Stephen Tu

Shivaram Venkataraman

Proceedings of the 34th International Conference on Machine Learning, 2017

Deep Transfer Learning with Joint Adaptation Networks.

[BibT_eX]

[DOI]

Proceedings of the 34th International Conference on Machine Learning, 2017

How to Escape Saddle Points Efficiently.

[BibT_eX]

[DOI]

Proceedings of the 34th International Conference on Machine Learning, 2017

Real-Time Machine Learning: The Missing Pieces.

[BibT_eX]

[DOI]

Johann Schleier-Smith

Proceedings of the 16th Workshop on Hot Topics in Operating Systems, 2017

QuTE: Decentralized multiple testing on sensor networks with false discovery rate control.

[BibT_eX]

[DOI]

Proceedings of the 56th IEEE Annual Conference on Decision and Control, 2017

On the Learnability of Fully-Connected Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

Less than a Single Pass: Stochastically Controlled Stochastic Gradient.

[BibT_eX]

[DOI]

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016

Spectral Methods Meet EM: A Provably Optimal Algorithm for Crowdsourcing.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2016

A Lyapunov Analysis of Momentum Methods in Optimization.

[BibT_eX]

[DOI]

Ashia C. Wilson

CoRR, 2016

A Variational Perspective on Accelerated Methods in Optimization.

[BibT_eX]

[DOI]

Andre Wibisono

Ashia C. Wilson

CoRR, 2016

High-Dimensional Continuous Control Using Generalized Advantage Estimation.

[BibT_eX]

[DOI]

Proceedings of the 4th International Conference on Learning Representations, 2016

Function-Specific Mixing Times and Concentration Away from Equilibrium.

[BibT_eX]

[DOI]

CoRR, 2016

CYCLADES: Conflict-free Asynchronous Machine Learning.

[BibT_eX]

[DOI]

Xinghao Pan

Maximilian Lam

Stephen Tu

CoRR, 2016

SparkNet: Training Deep Networks in Spark.

[BibT_eX]

[DOI]

Proceedings of the 4th International Conference on Learning Representations, 2016

Universality of Mallows' and degeneracy of Kendall's kernels for rankings.

[BibT_eX]

[DOI]

CoRR, 2016

Deep Transfer Learning with Joint Adaptation Networks.

[BibT_eX]

[DOI]

Mingsheng Long

Jianmin Wang

CoRR, 2016

Unsupervised Domain Adaptation with Residual Transfer Networks.

[BibT_eX]

[DOI]

Mingsheng Long

Jianmin Wang

CoRR, 2016

Less than a Single Pass: Stochastically Controlled Stochastic Gradient Method.

[BibT_eX]

[DOI]

CoRR, 2016

Gradient Descent Converges to Minimizers.

[BibT_eX]

[DOI]

CoRR, 2016

Communication-efficient distributed statistical learning.

[BibT_eX]

[DOI]

Yun Yang

CoRR, 2016

Minimax Optimal Procedures for Locally Private Estimation.

[BibT_eX]

[DOI]

CoRR, 2016

Asymptotic behavior of ℓp-based Laplacian regularization in semi-supervised learning.

[BibT_eX]

[DOI]

CoRR, 2016

On Computational Thinking, Inferential Thinking and Data Science.

[BibT_eX]

[DOI]

Proceedings of the 28th ACM Symposium on Parallelism in Algorithms and Architectures, 2016

Unsupervised Domain Adaptation with Residual Transfer Networks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Local Maxima in the Likelihood of Gaussian Mixture Models: Structural Results and Algorithmic Consequences.

[BibT_eX]

[DOI]

Sivaraman Balakrishnan

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

L1-regularized Neural Networks are Improperly Learnable in Polynomial Time.

[BibT_eX]

[DOI]

Proceedings of the 33nd International Conference on Machine Learning, 2016

A Kernelized Stein Discrepancy for Goodness-of-fit Tests.

[BibT_eX]

[DOI]

Qiang Liu

Proceedings of the 33nd International Conference on Machine Learning, 2016

Gradient Descent Only Converges to Minimizers.

[BibT_eX]

[DOI]

Proceedings of the 29th Conference on Learning Theory, 2016

A Linearly-Convergent Stochastic L-BFGS Algorithm.

[BibT_eX]

[DOI]

Philipp Moritz

Robert Nishihara

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

The Constrained Laplacian Rank Algorithm for Graph-Based Clustering.

[BibT_eX]

[DOI]

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015

Optimal Rates for Zero-Order Convex Optimization: The Power of Two Function Evaluations.

[BibT_eX]

[DOI]

IEEE Trans. Inf. Theory, 2015

Nested Hierarchical Dirichlet Processes.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2015

Combinatorial Clustering and the Beta Negative Binomial Process.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2015

Distributed matrix completion and robust factorization.

[BibT_eX]

[DOI]

Ameet Talwalkar

J. Mach. Learn. Res., 2015

Learning Halfspaces and Neural Networks with Random Initialization.

[BibT_eX]

[DOI]

CoRR, 2015

ℓ1-regularized Neural Networks are Improperly Learnable in Polynomial Time.

[BibT_eX]

[DOI]

CoRR, 2015

Splash: User-friendly Programming Interface for Parallelizing Stochastic Algorithms.

[BibT_eX]

[DOI]

CoRR, 2015

On the Computational Complexity of High-Dimensional Bayesian Variable Selection.

[BibT_eX]

[DOI]

Yun Yang

CoRR, 2015

TuPAQ: An Efficient Planner for Large-scale Predictive Analytic Queries.

[BibT_eX]

[DOI]

CoRR, 2015

L1-Regularized Distributed Optimization: A Communication-Efficient Primal-Dual Framework.

[BibT_eX]

[DOI]

CoRR, 2015

Asynchronous Complex Analytics in a Distributed Dataflow Architecture.

[BibT_eX]

[DOI]

Ali Ghodsi

CoRR, 2015

Machine Learning and Databases: The Sound of Things to Come or a Cacophony of Hype?

[BibT_eX]

[DOI]

Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, Melbourne, Victoria, Australia, May 31, 2015

Computational Thinking, Inferential Thinking and "Big Data".

[BibT_eX]

[DOI]

Proceedings of the 34th ACM Symposium on Principles of Database Systems, 2015

Variational Consensus Monte Carlo.

[BibT_eX]

[DOI]

Maxim Rabinovich

Elaine Angelino

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Parallel Correlation Clustering on Big Graphs.

[BibT_eX]

[DOI]

Xinghao Pan

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Linear Response Methods for Accurate Covariance Estimates from Mean Field Variational Bayes.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

On the Accuracy of Self-Normalized Log-Linear Models.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Optimism-driven exploration for nonlinear systems.

[BibT_eX]

[DOI]

Teodor Mihai Moldovan

Sergey Levine

Pieter Abbeel

Proceedings of the IEEE International Conference on Robotics and Automation, 2015

Distributed Estimation of Generalized Matrix Rank: Efficient Algorithms and Lower Bounds.

[BibT_eX]

[DOI]

Proceedings of the 32nd International Conference on Machine Learning, 2015

Trust Region Policy Optimization.

[BibT_eX]

[DOI]

Proceedings of the 32nd International Conference on Machine Learning, 2015

A General Analysis of the Convergence of ADMM.

[BibT_eX]

[DOI]

Proceedings of the 32nd International Conference on Machine Learning, 2015

Adding vs. Averaging in Distributed Primal-Dual Optimization.

[BibT_eX]

[DOI]

Proceedings of the 32nd International Conference on Machine Learning, 2015

Learning Transferable Features with Deep Adaptation Networks.

[BibT_eX]

[DOI]

Proceedings of the 32nd International Conference on Machine Learning, 2015

Automating model search for large scale machine learning.

[BibT_eX]

[DOI]

Proceedings of the Sixth ACM Symposium on Cloud Computing, 2015

The Missing Piece in Complex Analytics: Low Latency, Scalable Model Management and Serving with Velox.

[BibT_eX]

[DOI]

Proceedings of the Seventh Biennial Conference on Innovative Data Systems Research, 2015

2014

Bayesian Nonnegative Matrix Factorization with Stochastic Variational Inference.

[BibT_eX]

[DOI]

John W. Paisley

Proceedings of the Handbook of Mixed Membership Models and Their Applications., 2014

Mixed Membership Matrix Factorization.

[BibT_eX]

[DOI]

David J. Weiss

Proceedings of the Handbook of Mixed Membership Models and Their Applications., 2014

Mixed Membership Models for Time Series.

[BibT_eX]

[DOI]

Emily B. Fox

Proceedings of the Handbook of Mixed Membership Models and Their Applications., 2014

Scaling Up Crowd-Sourcing to Very Large Datasets: A Case for Active Learning.

[BibT_eX]

[DOI]

Proc. VLDB Endow., 2014

Iterative Discovery of Multiple AlternativeClustering Views.

[BibT_eX]

[DOI]

Donglin Niu

IEEE Trans. Pattern Anal. Mach. Intell., 2014

Particle gibbs with ancestor sampling.

[BibT_eX]

[DOI]

Fredrik Lindsten

Thomas B. Schön

J. Mach. Learn. Res., 2014

Privacy Aware Learning.

[BibT_eX]

[DOI]

J. ACM, 2014

SMaSH: a benchmarking toolkit for human genome variant calling.

[BibT_eX]

[DOI]

Bioinform., 2014

Knowing when you're wrong: building fast and reliable approximate query processing systems.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Management of Data, 2014

Changepoint Analysis for Efficient Variant Calling.

[BibT_eX]

[DOI]

Proceedings of the Research in Computational Molecular Biology, 2014

Parallel Double Greedy Submodular Maximization.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

On the Convergence Rate of Decomposable Submodular Function Minimization.

[BibT_eX]

[DOI]

Robert Nishihara

Stefanie Jegelka

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Communication-Efficient Distributed Dual Coordinate Ascent.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Lower bounds on the performance of polynomial-time algorithms for sparse linear regression.

[BibT_eX]

[DOI]

Proceedings of The 27th Conference on Learning Theory, 2014

Neural Networks.

[BibT_eX]

Proceedings of the Computing Handbook, 2014

2013

Cluster Forests.

[BibT_eX]

[DOI]

Donghui Yan

Aiyou Chen

Pedro A. d. F. R. Højen-Sørensen

Comput. Stat. Data Anal., 2013

Divide-and-Conquer Subspace Segmentation

[BibT_eX]

[DOI]

CoRR, 2013

A Nested HDP for Hierarchical Topic Models

[BibT_eX]

[DOI]

Proceedings of the 1st International Conference on Learning Representations, 2013

Variational MCMC

[BibT_eX]

[DOI]

Nando de Freitas

Stuart Russell

CoRR, 2013

On statistics, computation and scalability.

[BibT_eX]

[DOI]

CoRR, 2013

Mixed Membership Models for Time Series.

[BibT_eX]

[DOI]

Emily B. Fox

CoRR, 2013

Optimal rates for zero-order optimization: the power of two function evaluations.

[BibT_eX]

[DOI]

CoRR, 2013

Learning Dependency-Based Compositional Semantics.

[BibT_eX]

[DOI]

Comput. Linguistics, 2013

Bayesian semiparametric Wiener system identification.

[BibT_eX]

[DOI]

Fredrik Lindsten

Thomas B. Schön

Autom., 2013

Information-theoretic lower bounds for distributed statistical estimation with communication constraints.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

A Comparative Framework for Preconditioned Lasso Algorithms.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Optimistic Concurrency Control for Distributed Unsupervised Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Local Privacy and Minimax Bounds: Sharp Rates for Probability Estimation.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Estimation, Optimization, and Parallelism when Data is Sparse.

[BibT_eX]

[DOI]

H. Brendan McMahan

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Streaming Variational Bayes.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

A general bootstrap performance diagnostic.

[BibT_eX]

[DOI]

Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013

Efficient Ranking from Pairwise Comparisons.

[BibT_eX]

[DOI]

Proceedings of the 30th International Conference on Machine Learning, 2013

MAD-Bayes: MAP-based Asymptotic Derivations from Bayes.

[BibT_eX]

[DOI]

Brian Kulis

Proceedings of the 30th International Conference on Machine Learning, 2013

MLI: An API for Distributed Machine Learning.

[BibT_eX]

[DOI]

Proceedings of the 2013 IEEE 13th International Conference on Data Mining, 2013

Distributed Low-Rank Subspace Segmentation.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Computer Vision, 2013

Local Privacy and Statistical Minimax Rates.

[BibT_eX]

[DOI]

Proceedings of the 54th Annual IEEE Symposium on Foundations of Computer Science, 2013

MLbase: A Distributed Machine-learning System.

[BibT_eX]

[DOI]

Proceedings of the Sixth Biennial Conference on Innovative Data Systems Research, 2013

2012

Ergodic Mirror Descent.

[BibT_eX]

[DOI]

SIAM J. Optim., 2012

Qualcomm Context-Awareness Symposium Sets Research Agenda for Context-Aware Smartphones.

[BibT_eX]

[DOI]

Deborah L. McGuinness

IEEE Pervasive Comput., 2012

EP-GIG Priors and Applications in Bayesian Sparse Learning.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2012

Coherence functions with applications in large-margin classification methods.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2012

Stick-Breaking Beta Processes and the Poisson Process.

[BibT_eX]

[DOI]

John W. Paisley

Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Computational and Statistical Tradeoffs via Convex Relaxation

[BibT_eX]

[DOI]

Venkat Chandrasekaran

CoRR, 2012

Active Learning for Crowd-Sourced Databases

[BibT_eX]

[DOI]

CoRR, 2012

Graph partition strategies for generalized mean field inference

[BibT_eX]

[DOI]

Stuart Russell

CoRR, 2012

The Asymptotics of Ranking Algorithms

[BibT_eX]

[DOI]

CoRR, 2012

Ancestor Sampling for Particle Gibbs.

[BibT_eX]

[DOI]

Fredrik Lindsten

Thomas B. Schön

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Small-Variance Asymptotics for Exponential Family Dirichlet Process Mixture Models.

[BibT_eX]

[DOI]

Ke Jiang

Brian Kulis

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Finite Sample Convergence Rates of Zero-Order Stochastic Optimization Methods.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Active spectral clustering via iterative uncertainty reduction.

[BibT_eX]

[DOI]

Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012

Divide-and-conquer and statistical inference for big data.

[BibT_eX]

[DOI]

Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012

Nonparametric Link Prediction in Dynamic Networks.

[BibT_eX]

[DOI]

Purnamrita Sarkar

Deepayan Chakrabarti

Proceedings of the 29th International Conference on Machine Learning, 2012

Variational Bayesian Inference with Stochastic Search.

[BibT_eX]

[DOI]

John W. Paisley

Proceedings of the 29th International Conference on Machine Learning, 2012

Revisiting k-means: New Algorithms via Bayesian Nonparametrics.

[BibT_eX]

[DOI]

Brian Kulis

Proceedings of the 29th International Conference on Machine Learning, 2012

The Big Data Bootstrap.

[BibT_eX]

[DOI]

Proceedings of the 29th International Conference on Machine Learning, 2012

2011

Bayesian Nonparametric Inference of Switching Dynamic Linear Models.

[BibT_eX]

[DOI]

IEEE Trans. Signal Process., 2011

Learning Low-Dimensional Signal Models.

[BibT_eX]

[DOI]

IEEE Signal Process. Mag., 2011

Bayesian Generalized Kernel Mixed Models.

[BibT_eX]

[DOI]

Guang Dai

J. Mach. Learn. Res., 2011

Dimensionality Reduction for Spectral Clustering.

[BibT_eX]

[DOI]

Donglin Niu

Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

Nonparametric Combinatorial Sequence Models.

[BibT_eX]

[DOI]

J. Comput. Biol., 2011

Non-parametric Link Prediction

[BibT_eX]

[DOI]

Purnamrita Sarkar

Deepayan Chakrabarti

CoRR, 2011

Managing data transfers in computer clusters with orchestra.

[BibT_eX]

[DOI]

Proceedings of the ACM SIGCOMM 2011 Conference on Applications, 2011

Nonparametric Bayesian Co-clustering Ensembles.

[BibT_eX]

[DOI]

Proceedings of the Eleventh SIAM International Conference on Data Mining, 2011

Bayesian Bias Mitigation for Crowdsourcing.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Divide-and-Conquer Matrix Factorization.

[BibT_eX]

[DOI]

Ameet Talwalkar

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

A Unified Probabilistic Model for Global and Local Unsupervised Feature Selection.

[BibT_eX]

[DOI]

Yue Guan

Proceedings of the 28th International Conference on Machine Learning, 2011

The SCADS Director: Scaling a Distributed Storage System Under Stringent Performance Requirements.

[BibT_eX]

[DOI]

Proceedings of the 9th USENIX Conference on File and Storage Technologies, 2011

Supervised hierarchical Pitman-Yor process for natural scene segmentation.

[BibT_eX]

[DOI]

Proceedings of the 24th IEEE Conference on Computer Vision and Pattern Recognition, 2011

Visually Relating Gene Expression and in vivo DNA Binding Data.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2011

2010

Estimating Divergence Functionals and the Likelihood Ratio by Convex Risk Minimization.

[BibT_eX]

[DOI]

IEEE Trans. Inf. Theory, 2010

Bayesian Nonparametric Methods for Learning Markov Switching Processes.

[BibT_eX]

[DOI]

IEEE Signal Process. Mag., 2010

Joint covariate selection and joint subspace selection for multiple classification problems.

[BibT_eX]

[DOI]

Guillaume Obozinski

Ben Taskar

Stat. Comput., 2010

Neighbor-Dependent Ramachandran Probability Distributions of Amino Acids Developed from a Hierarchical Dirichlet Process Model.

[BibT_eX]

[DOI]

Roland L. Dunbrack Jr.

PLoS Comput. Biol., 2010

Convex and Semi-Nonnegative Matrix Factorizations.

[BibT_eX]

[DOI]

Chris H. Q. Ding

Tao Li

IEEE Trans. Pattern Anal. Mach. Intell., 2010

Regularized Discriminant Analysis, Ridge Regression and Beyond.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2010

Bayesian Generalized Kernel Models.

[BibT_eX]

[DOI]

Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Matrix-Variate Dirichlet Process Mixture Models.

[BibT_eX]

[DOI]

Guang Dai

Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Inference and Learning in Networks of Queues.

[BibT_eX]

[DOI]

Charles Sutton

Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

The nested chinese restaurant process and bayesian nonparametric inference of topic hierarchies.

[BibT_eX]

[DOI]

Thomas L. Griffiths

J. ACM, 2010

Bayesian Inference in Queueing Networks

[BibT_eX]

[DOI]

Charles Sutton

CoRR, 2010

Active site prediction using evolutionary and structural information.

[BibT_eX]

[DOI]

Bioinform., 2010

Modeling Events with Cascades of Poisson Processes.

[BibT_eX]

[DOI]

Aleksandr Simma

Proceedings of the UAI 2010, 2010

Experience Mining Google's Production Console Logs.

[BibT_eX]

[DOI]

Wei Xu

Proceedings of the Workshop on Managing Systems via Log Analysis and Machine Learning Techniques, 2010

Heavy-Tailed Process Priors for Selective Shrinkage.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Unsupervised Kernel Dimension Reduction.

[BibT_eX]

[DOI]

Meihong Wang

Fei Sha

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Random Conic Pursuit for Semidefinite Programming.

[BibT_eX]

[DOI]

Ariel Kleiner

Ali Rahimi

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Variational Inference over Combinatorial Spaces.

[BibT_eX]

[DOI]

Alexandre Bouchard-Côté

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Tree-Structured Stick Breaking for Hierarchical Data.

[BibT_eX]

[DOI]

Ryan Prescott Adams

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Type-Based MCMC.

[BibT_eX]

[DOI]

Proceedings of the Human Language Technologies: Conference of the North American Chapter of the Association of Computational Linguistics, 2010

An Analysis of the Convergence of Graph Laplacians.

[BibT_eX]

[DOI]

Daniel Ting

Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

Multiple Non-Redundant Spectral Clustering Views.

[BibT_eX]

[DOI]

Donglin Niu

Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

Mixed Membership Matrix Factorization.

[BibT_eX]

[DOI]

David J. Weiss

Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

Learning Programs: A Hierarchical Bayesian Approach.

[BibT_eX]

[DOI]

Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

On the Consistency of Ranking Algorithms.

[BibT_eX]

[DOI]

Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

Sufficient dimension reduction for visual sequence classification.

[BibT_eX]

[DOI]

Alex Shyr

Raquel Urtasun

Proceedings of the Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition, 2010

Characterizing, modeling, and generating workload spikes for stateful services.

[BibT_eX]

[DOI]

Proceedings of the 1st ACM Symposium on Cloud Computing, 2010

2009

Coherence Functions for Multicategory Margin-based Classification Methods.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

Latent Variable Models for Dimensionality Reduction.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

Joint estimation of gene conversion rates and mean conversion tract lengths from population SNP data.

[BibT_eX]

[DOI]

Junming Yin

Yun S. Song

Bioinform., 2009

Optimization of Structured Mean Field Objectives.

[BibT_eX]

[DOI]

Alexandre Bouchard-Côté

Proceedings of the UAI 2009, 2009

Detecting large-scale system problems by mining console logs.

[BibT_eX]

[DOI]

Proceedings of the 22nd ACM Symposium on Operating Systems Principles 2009, 2009

Combinatorial stochastic processes and nonparametric Bayesian modeling.

[BibT_eX]

[DOI]

Proceedings of the Twentieth Annual ACM-SIAM Symposium on Discrete Algorithms, 2009

A Flexible and Efficient Algorithm for Regularized Fisher Discriminant Analysis.

[BibT_eX]

[DOI]

Guang Dai

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2009

Nonparametric Latent Feature Models for Link Prediction.

[BibT_eX]

[DOI]

Kurt T. Miller

Thomas L. Griffiths

Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Asymptotically Optimal Regularization in Smooth Parametric Models.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Sharing Features among Dynamical Systems with Beta Processes.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Fast approximate spectral clustering.

[BibT_eX]

[DOI]

Donghui Yan

Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Paris, France, June 28, 2009

Learning from measurements in exponential families.

[BibT_eX]

[DOI]

Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Online System Problem Detection by Mining Patterns of Console Logs.

[BibT_eX]

[DOI]

Proceedings of the ICDM 2009, 2009

Predicting Multiple Metrics for Queries: Better Decisions Enabled by Machine Learning.

[BibT_eX]

[DOI]

Proceedings of the 25th International Conference on Data Engineering, 2009

Automatic exploration of datacenter performance regimes.

[BibT_eX]

[DOI]

Proceedings of the 1st Workshop on Automated Control for Datacenters and Clouds, 2009

Statistical Machine Learning Makes Automatic Control Practical for Internet Datacenters.

[BibT_eX]

[DOI]

Proceedings of the Workshop on Hot Topics in Cloud Computing, 2009

Learning Semantic Correspondences with Less Supervision.

[BibT_eX]

[DOI]

Proceedings of the ACL 2009, 2009

2008

On Optimal Quantization Rules for Some Problems in Sequential Decentralized Detection.

[BibT_eX]

[DOI]

IEEE Trans. Inf. Theory, 2008

A Dual Receptor Crosstalk Model of G-Protein-Coupled Signal Transduction.

[BibT_eX]

[DOI]

Patrick Flaherty

Mala L. Radhakrishnan

PLoS Comput. Biol., 2008

Graphical Models, Exponential Families, and Variational Inference.

[BibT_eX]

[DOI]

Found. Trends Mach. Learn., 2008

The Phylogenetic Indian Buffet Process: A Non-Exchangeable Nonparametric Prior for Latent Features.

[BibT_eX]

[DOI]

Kurt T. Miller

Thomas L. Griffiths

Proceedings of the UAI 2008, 2008

On the Inference of Ancestries in Admixed Populations.

[BibT_eX]

[DOI]

Proceedings of the Research in Computational Molecular Biology, 2008

Mining Console Logs for Large-Scale System Problem Detection.

[BibT_eX]

[DOI]

Proceedings of the Third Workshop on Tackling Computer Systems Problems with Machine Learning Techniques, 2008

Probabilistic Inference in Queueing Networks.

[BibT_eX]

[DOI]

Charles Sutton

Proceedings of the Third Workshop on Tackling Computer Systems Problems with Machine Learning Techniques, 2008

Posterior Consistency of the Silverman g-prior in Bayesian Model Choice.

[BibT_eX]

[DOI]

Dit-Yan Yeung

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Shared Segmentation of Natural Scenes Using Dependent Pitman-Yor Processes.

[BibT_eX]

[DOI]

Erik B. Sudderth

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

High-dimensional support union recovery in multivariate regression.

[BibT_eX]

[DOI]

Guillaume Obozinski

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

DiscLDA: Discriminative Learning for Dimensionality Reduction and Classification.

[BibT_eX]

[DOI]

Simon Lacoste-Julien

Fei Sha

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Spectral Clustering with Perturbed Data.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Nonparametric Bayesian Learning of Switching Linear Dynamical Systems.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Efficient Inference in Phylogenetic InDel Trees.

[BibT_eX]

[DOI]

Alexandre Bouchard-Côté

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

An asymptotic analysis of generative, discriminative, and pseudolikelihood estimators.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning, 2008

An HDP-HMM for systems with state persistence.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning, 2008

Nonnegative Matrix Factorization for Combinatorial Optimization: Spectral Clustering, Graph Matching, and Clique Finding.

[BibT_eX]

[DOI]

Chris H. Q. Ding

Tao Li

Proceedings of the 8th IEEE International Conference on Data Mining (ICDM 2008), 2008

Union support recovery in high-dimensional multivariate regression.

[BibT_eX]

[DOI]

Guillaume Obozinski

Proceedings of the 46th Annual Allerton Conference on Communication, 2008

2007

A Direct Formulation for Sparse PCA Using Semidefinite Programming.

[BibT_eX]

[DOI]

Alexandre d'Aspremont

SIAM Rev., 2007

Hierarchical Beta Processes and the Indian Buffet Process.

[BibT_eX]

[DOI]

Romain Thibaux

Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007

Bayesian Haplotype Inference via the Dirichlet Process.

[BibT_eX]

[DOI]

Roded Sharan

J. Comput. Biol., 2007

Estimating divergence functionals and the likelihood ratio by penalized convex risk minimization.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Agreement-Based Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Feature Selection Methods for Improving Protein Structure Prediction with Rosetta.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Nonparametric estimation of the likelihood ratio and divergence functionals.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Information Theory, 2007

Communication-Efficient Online Detection of Network-Wide Anomalies.

[BibT_eX]

[DOI]

Minos N. Garofalakis

Anthony D. Joseph

Nina Taft

Proceedings of the INFOCOM 2007. 26th IEEE International Conference on Computer Communications, 2007

Regression on manifolds using kernel dimension reduction.

[BibT_eX]

[DOI]

Jens Nilsson

Fei Sha

Proceedings of the Machine Learning, 2007

A permutation-augmented sampler for DP mixture models.

[BibT_eX]

[DOI]

Benjamin Taskar

Proceedings of the Machine Learning, 2007

Image Denoising with Nonparametric Hidden Markov Trees.

[BibT_eX]

[DOI]

Jyri J. Kivinen

Erik B. Sudderth

Proceedings of the International Conference on Image Processing, 2007

Solving Consensus and Semi-supervised Clustering Problems Using Nonnegative Matrix Factorization.

[BibT_eX]

[DOI]

Tao Li

Chris H. Q. Ding

Proceedings of the 7th IEEE International Conference on Data Mining (ICDM 2007), 2007

Learning Multiscale Representations of Natural Scenes Using Dirichlet Processes.

[BibT_eX]

[DOI]

Jyri J. Kivinen

Erik B. Sudderth

Proceedings of the IEEE 11th International Conference on Computer Vision, 2007

The Infinite PCFG Using Hierarchical Dirichlet Processes.

[BibT_eX]

[DOI]

Proceedings of the EMNLP-CoNLL 2007, 2007

Statistical Machine Learning and Computational Biology.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2007

2006

Log-determinant relaxation for approximate inference in discrete Markov random fields.

[BibT_eX]

[DOI]

IEEE Trans. Signal Process., 2006

Nonparametric empirical Bayes for the Dirichlet process mixture model.

[BibT_eX]

[DOI]

Jon D. McAuliffe

Stat. Comput., 2006

Structured Prediction, Dual Extragradient and Bregman Projections.

[BibT_eX]

[DOI]

Benjamin Taskar

Simon Lacoste-Julien

J. Mach. Learn. Res., 2006

Learning Spectral Clustering, With Application To Speech Separation.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2006

On optimal quantization rules for some sequential decision problems

[BibT_eX]

[DOI]

CoRR, 2006

Statistical modeling of biomedical corpora: mining the Caenorhabditis Genetic Center Bibliography for genes related to life span.

[BibT_eX]

[DOI]

BMC Bioinform., 2006

Bayesian Multicategory Support Vector Machines.

[BibT_eX]

[DOI]

Proceedings of the UAI '06, 2006

In-Network PCA and Anomaly Detection.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Word Alignment via Quadratic Assignment.

[BibT_eX]

[DOI]

Proceedings of the Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics, 2006

On optimal quantization rules for sequential decision problems.

[BibT_eX]

[DOI]

Proceedings of the Proceedings 2006 IEEE International Symposium on Information Theory, 2006

Statistical debugging: simultaneous identification of multiple bugs.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning, 2006

Bayesian multi-population haplotype inference via a hierarchical dirichlet process mixture.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning, 2006

A graphical model for predicting protein molecular function.

[BibT_eX]

[DOI]

Barbara E. Engelhardt

Steven E. Brenner

Proceedings of the Machine Learning, 2006

Gaussian Processes and the Null-Category Noise Model.

[BibT_eX]

[DOI]

Proceedings of the Semi-Supervised Learning, 2006

2005

Nonparametric decentralized detection using kernel methods.

[BibT_eX]

[DOI]

IEEE Trans. Signal Process., 2005

A kernel-based learning approach to ad hoc sensor network localization.

[BibT_eX]

[DOI]

Bruno Sinopoli

ACM Trans. Sens. Networks, 2005

Protein Molecular Function Prediction by Bayesian Phylogenomics.

[BibT_eX]

[DOI]

Barbara E. Engelhardt

Kathryn E. Muratore

Steven E. Brenner

PLoS Comput. Biol., 2005

On divergences, surrogate loss functions, and decentralized detection

[BibT_eX]

[DOI]

CoRR, 2005

A latent variable model for chemogenomic profiling.

[BibT_eX]

[DOI]

Bioinform., 2005

The DLR Hierarchy of Approximate Inference.

[BibT_eX]

[DOI]

Michal Rosen-Zvi

Alan L. Yuille

Proceedings of the UAI '05, 2005

Scalable statistical bug isolation.

[BibT_eX]

[DOI]

Proceedings of the ACM SIGPLAN 2005 Conference on Programming Language Design and Implementation, 2005

Structured Prediction via the Extragradient Method.

[BibT_eX]

[DOI]

Benjamin Taskar

Simon Lacoste-Julien

Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

Divergences, surrogate loss functions and experimental design.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

Robust design of biological experiments.

[BibT_eX]

[DOI]

Patrick Flaherty

Adam P. Arkin

Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

Predictive low-rank decomposition for kernel methods.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning, 2005

Multi-instrument musical transcription using a dynamic graphical model.

[BibT_eX]

[DOI]

Brian K. Vogel

David Wessel

Proceedings of the 2005 IEEE International Conference on Acoustics, 2005

Discriminative training of hidden Markov models for multiple pitch tracking [speech processing examples].

[BibT_eX]

[DOI]

Proceedings of the 2005 IEEE International Conference on Acoustics, 2005

Combining Visualization and Statistical Analysis to Improve Operator Confidence and Efficiency for Failure Detection and Localization.

[BibT_eX]

[DOI]

Proceedings of the Second International Conference on Autonomic Computing (ICAC 2005), 2005

Modèles de Markov cachés pour l'estimation de plusieurs fréquences fondamentales.

[BibT_eX]

[DOI]

Proceedings of the Extraction des connaissances : Etat et perspectives (Ateliers de la conférence EGC'2005), 2005

Semiparametric latent factor models.

[BibT_eX]

[DOI]

Yee Whye Teh

Matthias W. Seeger

Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, 2005

2004

Learning graphical models for stationary time series.

[BibT_eX]

[DOI]

IEEE Trans. Signal Process., 2004

Kalman filtering with intermittent observations.

[BibT_eX]

[DOI]

Bruno Sinopoli

Luca Schenato

Massimo Franceschetti

Kameshwar Poolla

Shankar S. Sastry

IEEE Trans. Autom. Control., 2004

Learning the Kernel Matrix with Semidefinite Programming.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2004

Dimensionality Reduction for Supervised Learning with Reproducing Kernel Hilbert Spaces.

[BibT_eX]

[DOI]

Kenji Fukumizu

J. Mach. Learn. Res., 2004

Robust Sparse Hyperplane Classifiers: Application to Uncertain Molecular Profiling Data.

[BibT_eX]

[DOI]

J. Comput. Biol., 2004

Logos: a Modular Bayesian Model for de Novo Motif Detection.

[BibT_eX]

[DOI]

J. Bioinform. Comput. Biol., 2004

Multiple-sequence functional annotation and the generalized hidden Markov phylogeny.

[BibT_eX]

[DOI]

Jon D. McAuliffe

Lior Pachter

Bioinform., 2004

A statistical framework for genomic data fusion.

[BibT_eX]

[DOI]

William Stafford Noble

Bioinform., 2004

Graph Partition Strategies for Generalized Mean Field Inference.

[BibT_eX]

[DOI]

Proceedings of the UAI '04, 2004

Kernel-Based Data Fusion and Its Application to Protein Function Prediction in Yeast.

[BibT_eX]

[DOI]

William Stafford Noble

Proceedings of the Biocomputing 2004, 2004

Sharing Clusters among Related Groups: Hierarchical Dirichlet Processes.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Semi-supervised Learning via Gaussian Processes.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Computing regularization paths for learning multiple kernels.

[BibT_eX]

[DOI]

Romain Thibaux

Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Blind One-microphone Speech Separation: A Spectral Learning Approach.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Bayesian haplo-type inference via the dirichlet process.

[BibT_eX]

[DOI]

Roded Sharan

Proceedings of the Machine Learning, 2004

Decentralized detection and classification using kernel methods.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning, 2004

Variational methods for the Dirichlet process.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning, 2004

Multiple kernel learning, conic duality, and the SMO algorithm.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning, 2004

Failure Diagnosis Using Decision Trees.

[BibT_eX]

[DOI]

Proceedings of the 1st International Conference on Autonomic Computing (ICAC 2004), 2004

Extensions of the Informative Vector Machine.

[BibT_eX]

[DOI]

John C. Platt

Proceedings of the Deterministic and Statistical Methods in Machine Learning, 2004

2003

Simultaneous classification and relevant feature identification in high-dimensional spaces: application to molecular profiling data.

[BibT_eX]

[DOI]

Signal Process., 2003

An Introduction to MCMC for Machine Learning.

[BibT_eX]

[DOI]

Mach. Learn., 2003

Latent Dirichlet Allocation.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2003

Matching Words and Pictures.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2003

Beyond Independent Components: Trees and Clusters.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2003

A generalized mean field algorithm for variational inference in exponential families.

[BibT_eX]

[DOI]

Stuart Russell

Proceedings of the UAI '03, 2003

Modeling annotated data.

[BibT_eX]

[DOI]

Proceedings of the SIGIR 2003: Proceedings of the 26th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, July 28, 2003

Bug isolation via remote program sampling.

[BibT_eX]

[DOI]

Proceedings of the ACM SIGPLAN 2003 Conference on Programming Language Design and Implementation 2003, 2003

Statistical Debugging of Sampled Programs.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Semidefinite Relaxations for Approximate Inference on Graphs with Cycles.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

On the Concentration of Expectation and Approximate Inference in Layered Networks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Autonomous Helicopter Flight via Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Kernel Dimensionality Reduction for Supervised Learning.

[BibT_eX]

[DOI]

Kenji Fukumizu

Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Hierarchical Topic Models and the Nested Chinese Restaurant Process.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Large Margin Classifiers: Convex Loss, Low Noise, and Convergence Rates.

[BibT_eX]

[DOI]

Jon D. McAuliffe

Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Learning Spectral Clustering.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Support vector machines for analog circuit performance representation.

[BibT_eX]

[DOI]

Fernando De Bernardinis

Alberto L. Sangiovanni-Vincentelli

Proceedings of the 40th Design Automation Conference, 2003

LOGOS: a modular Bayesian model for de novo motif detection.

[BibT_eX]

[DOI]

Proceedings of the 2nd IEEE Computer Society Bioinformatics Conference, 2003

2002

Graphical Models: Foundations of Neural Computation.

[BibT_eX]

[DOI]

Terrence J. Sejnowski

Pattern Anal. Appl., 2002

A Robust Minimax Approach to Classification.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2002

Kernel Independent Component Analysis.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2002

Simultaneous Relevant Feature Identification and Classification in High-Dimensional Spaces.

[BibT_eX]

[DOI]

L. R. Grate

I. Saira Mian

Proceedings of the Algorithms in Bioinformatics, Second International Workshop, 2002

Loopy Belief Propogation and Gibbs Measures.

[BibT_eX]

[DOI]

Sekhar Tatikonda

Proceedings of the UAI '02, 2002

Tree-dependent Component Analysis.

[BibT_eX]

[DOI]

Proceedings of the UAI '02, 2002

Distance Metric Learning with Application to Clustering with Side-Information.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

A Hierarchical Bayesian Markovian Model for Motifs in Biopolymer Sequences.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

A Minimal Intervention Principle for Coordinated Movement.

[BibT_eX]

[DOI]

Emanuel Todorov

Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

Robust Novelty Detection with Single-Class MPM.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

Learning Graphical Models with Mercer Kernels.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

Learning the Kernel Matrix with Semi-Definite Programming.

[BibT_eX]

Proceedings of the Machine Learning, 2002

2001

Asymptotic Convergence Rate of the EM Algorithm for Gaussian Mixtures.

[BibT_eX]

[DOI]

Jinwen Ma

Neural Comput., 2001

Efficient Stepwise Selection in Decomposable Models.

[BibT_eX]

[DOI]

Amol Deshpande

Minos N. Garofalakis

Proceedings of the UAI '01: Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence, 2001

Stable Algorithms for Link Analysis.

[BibT_eX]

[DOI]

Alice X. Zheng

Proceedings of the SIGIR 2001: Proceedings of the 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2001

On Spectral Clustering: Analysis and an algorithm.

[BibT_eX]

[DOI]

Yair Weiss

Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

On Discriminative vs. Generative Classifiers: A comparison of logistic regression and naive Bayes.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

Minimax Probability Machine.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

Thin Junction Trees.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

Link Analysis, Eigenvectors and Stability.

[BibT_eX]

Alice X. Zheng

Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence, 2001

Feature selection for high-dimensional genomic microarray data.

[BibT_eX]

Richard M. Karp

Proceedings of the Eighteenth International Conference on Machine Learning (ICML 2001), Williams College, Williamstown, MA, USA, June 28, 2001

Convergence rates of the Voting Gibbs classifier, with application to Bayesian feature selection.

[BibT_eX]

Proceedings of the Eighteenth International Conference on Machine Learning (ICML 2001), Williams College, Williamstown, MA, USA, June 28, 2001

2000

Bayesian parameter estimation via variational methods.

[BibT_eX]

[DOI]

Stat. Comput., 2000

Attractor Dynamics in Feedforward Neural Networks.

[BibT_eX]

[DOI]

Neural Comput., 2000

Learning with Mixtures of Trees.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2000

PEGASUS: A policy search method for large MDPs and POMDPs.

[BibT_eX]

[DOI]

Proceedings of the UAI '00: Proceedings of the 16th Conference in Uncertainty in Artificial Intelligence, Stanford University, Stanford, California, USA, June 30, 2000

1999

Mixed Memory Markov Models: Decomposing Complex Stochastic Processes as Mixtures of Simpler Ones.

[BibT_eX]

[DOI]

Mach. Learn., 1999

An Introduction to Variational Methods for Graphical Models.

[BibT_eX]

[DOI]

Mach. Learn., 1999

Variational Probabilistic Inference and the QMR-DT Network.

[BibT_eX]

[DOI]

J. Artif. Intell. Res., 1999

Loopy Belief Propagation for Approximate Inference: An Empirical Study.

[BibT_eX]

[DOI]

Kevin P. Murphy

Yair Weiss

Proceedings of the UAI '99: Proceedings of the Fifteenth Conference on Uncertainty in Artificial Intelligence, Stockholm, Sweden, July 30, 1999

Approximate Inference A lgorithms for Two-Layer Bayesian Networks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

1998

Mixture Representations for Inference and Learning in Boltzmann Machines.

[BibT_eX]

[DOI]

Proceedings of the UAI '98: Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, 1998

Learning from Dyadic Data.

[BibT_eX]

[DOI]

Thomas Hofmann

Jan Puzicha

Proceedings of the Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30, 1998

A Mean Field Learning Algorithm for Unsupervised Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Learning in Graphical Models, 1998

An Introduction to Variational Methods for Graphical Models.

[BibT_eX]

[DOI]

Proceedings of the Learning in Graphical Models, 1998

Improving the Mean Field Approximation Via the Use of Mixture Distributions.

[BibT_eX]

[DOI]

Proceedings of the Learning in Graphical Models, 1998

1997

Probabilistic Independence Networks for Hidden Markov Probability Models.

[BibT_eX]

[DOI]

Padhraic Smyth

David Heckerman

Neural Comput., 1997

Factorial Hidden Markov Models.

[BibT_eX]

[DOI]

Mach. Learn., 1997

Estimating Dependency Structure as a Hidden Variable.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 10, 1997

Adaptation in Speech Motor Control.

[BibT_eX]

[DOI]

John F. Houde

Proceedings of the Advances in Neural Information Processing Systems 10, 1997

Approximating Posterior Distributions in Belief Networks Using Mixtures.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 10, 1997

Neural Networks.

[BibT_eX]

Proceedings of the Computer Science and Engineering Handbook, 1997

1996

Local linear perceptrons for classification.

[BibT_eX]

[DOI]

Ethem Alpaydin

IEEE Trans. Neural Networks, 1996

On Convergence Properties of the EM Algorithm for Gaussian Mixtures.

[BibT_eX]

[DOI]

Neural Comput., 1996

Mean Field Theory for Sigmoid Belief Networks.

[BibT_eX]

[DOI]

J. Artif. Intell. Res., 1996

Active Learning with Statistical Models.

[BibT_eX]

[DOI]

David A. Cohn

J. Artif. Intell. Res., 1996

Neural Networks.

[BibT_eX]

[DOI]

ACM Comput. Surv., 1996

Computing upper and lower bounds on likelihoods in intractable networks.

[BibT_eX]

[DOI]

Proceedings of the UAI '96: Proceedings of the Twelfth Annual Conference on Uncertainty in Artificial Intelligence, 1996

A Variational Principle for Model-based Morphing.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 9, 1996

Triangulation by Continuous Embedding.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 9, 1996

Hidden Markov Decision Trees.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 9, 1996

Recursive Algorithms for Approximating Probabilities in Graphical Models.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 9, 1996

1995

Convergence results for the EM approach to mixtures of experts architectures.

[BibT_eX]

[DOI]

Neural Networks, 1995

Exploiting Tractable Substructures in Intractable Networks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 8, 1995

Reinforcement Learning by Probability Matching.

[BibT_eX]

[DOI]

Philip N. Sabes

Proceedings of the Advances in Neural Information Processing Systems 8, 1995

Learning Fine Motion by Markov Mixtures of Experts.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 8, 1995

Fast Learning by Bounding Likelihoods in Sigmoid Type Belief Networks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 8, 1995

1994

Learning in Boltzmann Trees.

[BibT_eX]

[DOI]

Neural Comput., 1994

Hierarchical Mixtures of Experts and the EM Algorithm.

[BibT_eX]

[DOI]

Neural Comput., 1994

On the Convergence of Stochastic Iterative Dynamic Programming Algorithms.

[BibT_eX]

[DOI]

Satinder P. Singh

Neural Comput., 1994

An Alternative Model for Mixtures of Experts.

[BibT_eX]

[DOI]

Geoffrey E. Hinton

Proceedings of the Advances in Neural Information Processing Systems 7, 1994

Forward dynamic models in human motor control: Psychophysical evidence.

[BibT_eX]

[DOI]

Daniel M. Wolpert

Proceedings of the Advances in Neural Information Processing Systems 7, 1994

Reinforcement Learning with Soft State Aggregation.

[BibT_eX]

[DOI]

Satinder Singh

Proceedings of the Advances in Neural Information Processing Systems 7, 1994

Boltzmann Chains and Hidden Markov Models.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 7, 1994

Reinforcement Learning Algorithm for Partially Observable Markov Decision Problems.

[BibT_eX]

[DOI]

Satinder Singh

Proceedings of the Advances in Neural Information Processing Systems 7, 1994

Computational Structure of coordinate transformations: A generalization study.

[BibT_eX]

[DOI]

Daniel M. Wolpert

Proceedings of the Advances in Neural Information Processing Systems 7, 1994

Learning Without State-Estimation in Partially Observable Markovian Decision Processes.

[BibT_eX]

[DOI]

Satinder P. Singh

Proceedings of the Machine Learning, 1994

A Statistical Approach to Decision Tree Modeling.

[BibT_eX]

[DOI]

Proceedings of the Seventh Annual ACM Conference on Computational Learning Theory, 1994

1993

Learning piecewise control strategies in a modular neural network architecture.

[BibT_eX]

[DOI]

IEEE Trans. Syst. Man Cybern., 1993

Task Decompostiion Through Competition in a Modular Connectionist Architecture: The What and Where Vision Tasks.

[BibT_eX]

[DOI]

Andrew G. Barto

Proceedings of the Machine Learning: From Theory to Applications, 1993

Supervised learning from incomplete data via an EM approach.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 6, 1993

Supervised Learning and Divide-and-Conquer: A Statistical Approach.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning, 1993

1992

Forward Models: Supervised Learning with a Distal Teacher.

[BibT_eX]

[DOI]

David E. Rumelhart

Cogn. Sci., 1992

A Dynamical Model of Priming and Repetition Blindness.

[BibT_eX]

[DOI]

Daphne Bavelier

Proceedings of the Advances in Neural Information Processing Systems 5, [NIPS Conference, Denver, Colorado, USA, November 30, 1992

1991

Adaptive Mixtures of Local Experts.

[BibT_eX]

[DOI]

Neural Comput., 1991

Task Decomposition Through Competition in a Modular Connectionist Architecture: The What and Where Vision Tasks.

[BibT_eX]

[DOI]

Andrew G. Barto

Cogn. Sci., 1991

Hierarchies of Adaptive Experts.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 4, 1991

Forward Dynamics Modeling of Speech Motor Control Using Physiological Data.

[BibT_eX]

[DOI]

Makoto Hirayama

Eric Vatikiotis-Bateson

Mitsuo Kawato

Proceedings of the Advances in Neural Information Processing Systems 4, 1991

Internal World Models and Supervised Learning.

[BibT_eX]

[DOI]

David E. Rumelhart

Proceedings of the Eighth International Workshop (ML91), 1991

1990

A Competitive Modular Connectionist Architecture.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 3, 1990

A R-P learning applied to a network model of cortical area 7a.

[BibT_eX]

[DOI]

Pietro Mazzoni

Richard A. Andersen

Proceedings of the IJCNN 1990, 1990

1989

Learning to Control an Unstable System with Forward Modeling.

[BibT_eX]

[DOI]