Yu-Xiang Wang

CoRR, 2024

2023

Communication-Efficient Federated Non-Linear Bandit Optimization.

[BibT_eX]

[DOI]

Chuanhao Li

CoRR, 2023

On the accuracy and efficiency of group-wise clipping in differentially private optimization.

[BibT_eX]

[DOI]

CoRR, 2023

Posterior Sampling with Delayed Feedback for Reinforcement Learning with Linear Function Approximation.

[BibT_eX]

[DOI]

CoRR, 2023

Tractable MCMC for Private Learning with Pure and Gaussian Differential Privacy.

[BibT_eX]

[DOI]

CoRR, 2023

Coupling public and private gradient provably helps optimization.

[BibT_eX]

[DOI]

CoRR, 2023

Threshold KNN-Shapley: A Linear-Time and Privacy-Friendly Approach to Data Valuation.

[BibT_eX]

[DOI]

CoRR, 2023

Model-Free Algorithm with Improved Sample Efficiency for Zero-Sum Markov Games.

[BibT_eX]

[DOI]

CoRR, 2023

Nonparametric Classification on Low Dimensional Manifolds using Overparameterized Convolutional Residual Networks.

[BibT_eX]

[DOI]

CoRR, 2023

Provable Robust Watermarking for AI-Generated Text.

[BibT_eX]

[DOI]

CoRR, 2023

Offline Policy Evaluation for Reinforcement Learning with Adaptively Collected Data.

[BibT_eX]

[DOI]

CoRR, 2023

Generative Autoencoders as Watermark Attackers: Analyses of Vulnerabilities and Threats.

[BibT_eX]

[DOI]

CoRR, 2023

Improved Differentially Private Regression via Gradient Boosting.

[BibT_eX]

[DOI]

CoRR, 2023

Logarithmic Switching Cost in Reinforcement Learning beyond Linear MDPs.

[BibT_eX]

[DOI]

CoRR, 2023

No-Regret Linear Bandits beyond Realizability.

[BibT_eX]

[DOI]

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Private Prediction Strikes Back! Private Kernelized Nearest Neighbors with Individual Rényi Filter.

[BibT_eX]

[DOI]

Proceedings of the Uncertainty in Artificial Intelligence, 2023

A Privacy-Friendly Approach to Data Valuation.

[BibT_eX]

[DOI]

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

Improving the Privacy and Practicality of Objective Perturbation for Differentially Private Linear Learners.

[BibT_eX]

[DOI]

Antti Koskela

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

Posterior Sampling with Delayed Feedback for Reinforcement Learning with Linear Function Approximation.

[BibT_eX]

[DOI]

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

Automatic Clipping: Differentially Private Deep Learning Made Easier and Stronger.

[BibT_eX]

[DOI]

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

Online Label Shift: Optimal Dynamic Regret meets Practical Algorithms.

[BibT_eX]

[DOI]

Saurabh Garg

Tzu-Ching Yen

Sivaraman Balakrishnan

Zachary C. Lipton

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

Protecting Language Generation Models via Invisible Watermarking.

[BibT_eX]

[DOI]

Lei Li

Proceedings of the International Conference on Machine Learning, 2023

Global Optimization with Parametric Function Approximation.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Offline Reinforcement Learning with Closed-Form Policy Improvement Operators.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Non-stationary Reinforcement Learning under General Function Approximation.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Differentially Private Optimization on Large Model at Small Cost.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Deep Learning meets Nonparametric Regression: Are Weight-Decayed DNNs Locally Adaptive?

[BibT_eX]

[DOI]

Kaiqi Zhang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Offline Reinforcement Learning with Differentiable Function Approximation is Provably Efficient.

[BibT_eX]

[DOI]

Mengdi Wang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Near-Optimal Deployment Efficiency in Reward-Free Reinforcement Learning with Linear Function Approximation.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Doubly Fair Dynamic Pricing.

[BibT_eX]

[DOI]

Jianyu Xu

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

Generalized PTR: User-Friendly Recipes for Data-Adaptive Algorithms with Differential Privacy.

[BibT_eX]

[DOI]

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

Second Order Path Variationals in Non-Stationary Online Learning.

[BibT_eX]

[DOI]

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

Near-Optimal Differentially Private Reinforcement Learning.

[BibT_eX]

[DOI]

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

2022

Doubly Robust Crowdsourcing.

[BibT_eX]

[DOI]

J. Artif. Intell. Res., 2022

Differentially Private Bias-Term only Fine-tuning of Foundation Models.

[BibT_eX]

[DOI]

CoRR, 2022

Why Quantization Improves Generalization: NTK of Binary Weight Neural Networks.

[BibT_eX]

[DOI]

Kaiqi Zhang

CoRR, 2022

Offline Reinforcement Learning with Differential Privacy.

[BibT_eX]

[DOI]

CoRR, 2022

Towards Differential Relational Privacy and its use in Question Answering.

[BibT_eX]

[DOI]

CoRR, 2022

Offline stochastic shortest path: Learning, evaluation and towards optimality.

[BibT_eX]

[DOI]

Proceedings of the Uncertainty in Artificial Intelligence, 2022

Differentially Private Linear Sketches: Efficient Implementations and Applications.

[BibT_eX]

[DOI]

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

SeqPATE: Differentially Private Text Generation via Knowledge Distillation.

[BibT_eX]

[DOI]

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

Optimal Dynamic Regret in LQR Control.

[BibT_eX]

[DOI]

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

Provably Confidential Language Modelling.

[BibT_eX]

[DOI]

Lei Li

Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

Sample-Efficient Reinforcement Learning with loglog(T) Switching Cost.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Near-optimal Offline Reinforcement Learning with Linear Representation: Leveraging Variance Information with Pessimism.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

Distillation-Resistant Watermarking for Model Protection in NLP.

[BibT_eX]

[DOI]

Lei Li

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Mixed Differential Privacy in Computer Vision.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Towards Agnostic Feature-based Dynamic Pricing: Linear Policies vs Linear Valuation with Unknown Noise.

[BibT_eX]

[DOI]

Jianyu Xu

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

Optimal Dynamic Regret in Proper Online Learning with Strongly Convex Losses and Beyond.

[BibT_eX]

[DOI]

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

Non-stationary Online Learning with Memory and Non-stochastic Control.

[BibT_eX]

[DOI]

Peng Zhao

Zhi-Hua Zhou

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

Adaptive Private-K-Selection with Adaptive K and Application to Multi-label PATE.

[BibT_eX]

[DOI]

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

Optimal Accounting of Differential Privacy via Characteristic Function.

[BibT_eX]

[DOI]

Jinshuo Dong

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

2021

Revisiting Model-Agnostic Private Learning: Faster Rates and Active Learning.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2021

Multivariate Trend Filtering for Lattice Data.

[BibT_eX]

[DOI]

Addison J. Hu

CoRR, 2021

Inter-Series Attention Model for COVID-19 Forecasting.

[BibT_eX]

[DOI]

Xiaoyong Jin

Xifeng Yan

Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

Optimal Uniform OPE and Model-based Offline Reinforcement Learning in Time-Homogeneous, Reward-Free and Task-Agnostic Settings.

[BibT_eX]

[DOI]

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

Towards Instance-Optimal Offline Reinforcement Learning with Pessimism.

[BibT_eX]

[DOI]

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

Near-Optimal Offline Reinforcement Learning via Double Variance Reduction.

[BibT_eX]

[DOI]

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

Logarithmic Regret in Feature-based Dynamic Pricing.

[BibT_eX]

[DOI]

Jianyu Xu

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

Privately Publishable Per-instance Privacy.

[BibT_eX]

[DOI]

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

Bullseye Polytope: A Scalable Clean-Label Poisoning Attack with Improved Transferability.

[BibT_eX]

[DOI]

Proceedings of the IEEE European Symposium on Security and Privacy, 2021

Optimal Dynamic Regret in Exp-Concave Online Learning.

[BibT_eX]

[DOI]

Proceedings of the Conference on Learning Theory, 2021

Near-Optimal Provable Uniform Convergence in Offline Policy Evaluation for Reinforcement Learning.

[BibT_eX]

[DOI]

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

An Optimal Reduction of TV-Denoising to Adaptive Online Learning.

[BibT_eX]

[DOI]

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

2020

Patch-Based Image Hallucination for Super Resolution With Detail Reconstruction From Similar Sample Images.

[BibT_eX]

[DOI]

IEEE Trans. Multim., 2020

Subsampled Rényi Differential Privacy and Analytical Moments Accountant.

[BibT_eX]

[DOI]

Shiva Prasad Kasiviswanathan

Borja Balle

J. Priv. Confidentiality, 2020

Voting-based Approaches For Differentially Private Federated Learning.

[BibT_eX]

[DOI]

CoRR, 2020

Near Optimal Provable Uniform Convergence in Off-Policy Evaluation for Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2020

Domain Adaptation with Conditional Distribution Matching and Generalized Label Shift.

[BibT_eX]

[DOI]

Remi Tachet des Combes

Han Zhao

Geoffrey J. Gordon

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

Adaptive Online Estimation of Piecewise Polynomial Trends.

[BibT_eX]

[DOI]

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

Improving Sparse Vector Technique with Renyi Differential Privacy.

[BibT_eX]

[DOI]

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

An end-to-end Differentially Private Latent Dirichlet Allocation Using a Spectral Algorithm.

[BibT_eX]

[DOI]

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

Private-kNN: Practical Differential Privacy for Computer Vision.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Asymptotically Efficient Off-Policy Evaluation for Tabular Reinforcement Learning.

[BibT_eX]

[DOI]

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

2019

Provable Subspace Clustering: When LRR Meets SSC.

[BibT_eX]

[DOI]

Huan Xu

Chenlei Leng

IEEE Trans. Inf. Theory, 2019

A Theoretical Analysis of Noisy Sparse Subspace Clustering on Dimensionality-Reduced Data.

[BibT_eX]

[DOI]

IEEE Trans. Inf. Theory, 2019

Per-instance Differential Privacy.

[BibT_eX]

[DOI]

J. Priv. Confidentiality, 2019

Technical Note - Nonstationary Stochastic Optimization Under Lp, q-Variation Measures.

[BibT_eX]

[DOI]

Xi Chen

Oper. Res., 2019

Optimal Off-Policy Evaluation for Reinforcement Learning with Marginalized Importance Sampling.

[BibT_eX]

[DOI]

Tengyang Xie

Yifei Ma

CoRR, 2019

Towards Optimal Off-Policy Evaluation for Reinforcement Learning with Marginalized Importance Sampling.

[BibT_eX]

[DOI]

Tengyang Xie

Yifei Ma

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

Enhancing the Locality and Breaking the Memory Bottleneck of Transformer on Time Series Forecasting.

[BibT_eX]

[DOI]

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

Provably Efficient Q-Learning with Low Switching Cost.

[BibT_eX]

[DOI]

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

Online Forecasting of Total-Variation-bounded Sequences.

[BibT_eX]

[DOI]

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

Poission Subsampled Rényi Differential Privacy.

[BibT_eX]

[DOI]

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

ProxQuant: Quantized Neural Networks via Proximal Operators.

[BibT_eX]

[DOI]

Edo Liberty

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

A Higher-Order Kolmogorov-Smirnov Test.

[BibT_eX]

[DOI]

Aaditya Ramdas

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

Imitation-Regularized Offline Learning.

[BibT_eX]

[DOI]

Yifei Ma

Balakrishnan Narayanaswamy

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

2018

Revisiting differentially private linear regression: optimal and adaptive prediction & estimation in unbounded domain.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Detecting and Correcting for Label Shift with Black Box Predictors.

[BibT_eX]

[DOI]

Zachary C. Lipton

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

SIGNSGD: Compressed Optimisation for Non-Convex Problems.

[BibT_eX]

[DOI]

Jeremy Bernstein

Kamyar Azizzadenesheli

Animashree Anandkumar

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

Improving the Gaussian Mechanism for Differential Privacy: Analytical Calibration and Optimal Denoising.

[BibT_eX]

[DOI]

Borja Balle

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

Compression by the signs: distributed learning is a two-way street.

[BibT_eX]

[DOI]

Jeremy Bernstein

Kamyar Azizzadenesheli

Anima Anandkumar

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

New Paradigms and Optimality Guarantees in Statistical Learning and Estimation.

[BibT_eX]

[DOI]

PhD thesis, 2017

Non-stationary Stochastic Optimization with Local Spatial and Temporal Changes.

[BibT_eX]

[DOI]

Xi Chen

CoRR, 2017

Per-instance Differential Privacy and the Adaptivity of Posterior Sampling in Linear and Ridge regression.

[BibT_eX]

[DOI]

CoRR, 2017

Higher-Order Total Variation Classes on Grids: Minimax Theory and Trend Filtering Methods.

[BibT_eX]

[DOI]

James Sharpnack

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

Optimal and Adaptive Off-policy Evaluation in Contextual Bandits.

[BibT_eX]

[DOI]

Alekh Agarwal

Miroslav Dudík

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

Attributing Hacks.

[BibT_eX]

[DOI]

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

2016

Noisy Sparse Subspace Clustering.

[BibT_eX]

[DOI]

Huan Xu

J. Mach. Learn. Res., 2016

Trend Filtering on Graphs.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2016

Learning with Differential Privacy: Stability, Learnability and the Sufficiency and Necessity of ERM Principle.

[BibT_eX]

[DOI]

Jing Lei

J. Mach. Learn. Res., 2016

A Minimax Theory for Adaptive Data Analysis.

[BibT_eX]

[DOI]

Jing Lei

CoRR, 2016

DiFacto: Distributed Factorization Machines.

[BibT_eX]

[DOI]

Proceedings of the Ninth ACM International Conference on Web Search and Data Mining, 2016

On-Average KL-Privacy and Its Equivalence to Generalization for Max-Entropy Mechanisms.

[BibT_eX]

[DOI]

Jing Lei

Proceedings of the Privacy in Statistical Databases, 2016

Total Variation Classes Beyond 1d: Minimax Rates, and the Limitations of Linear Smoothers.

[BibT_eX]

[DOI]

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

Parallel and Distributed Block-Coordinate Frank-Wolfe Algorithms.

[BibT_eX]

[DOI]

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

Graph Connectivity in Noisy Sparse Subspace Clustering.

[BibT_eX]

[DOI]

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

Graph Sparsification Approaches for Laplacian Smoothing.

[BibT_eX]

[DOI]

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

2015

Practical Matrix Completion and Corruption Recovery Using Proximal Alternating Robust Subspace Minimization.

[BibT_eX]

[DOI]

Int. J. Comput. Vis., 2015

Clustering Consistent Sparse Subspace Clustering.

[BibT_eX]

[DOI]

CoRR, 2015

Fast Differentially Private Matrix Factorization.

[BibT_eX]

[DOI]

Ziqi Liu

Proceedings of the 9th ACM Conference on Recommender Systems, 2015

Differentially private subspace clustering.

[BibT_eX]

[DOI]

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

Who Supported Obama in 2012?: Ecological Inference through Distribution Regression.

[BibT_eX]

[DOI]

Seth R. Flaxman

Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

A Deterministic Analysis of Noisy Sparse Subspace Clustering for Dimensionality-reduced Data.

[BibT_eX]

[DOI]

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

Privacy for Free: Posterior Sampling and Stochastic Gradient Monte Carlo.

[BibT_eX]

[DOI]

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

2014

Block-Sparse RPCA for Salient Motion Detection.

[BibT_eX]

[DOI]

Zhi Gao

Loong-Fah Cheong

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

The Falling Factorial Basis and Its Statistical Applications.

[BibT_eX]

[DOI]

Proceedings of the 31th International Conference on Machine Learning, 2014

2012

Stability of matrix factorization for collaborative filtering.

[BibT_eX]

[DOI]

Huan Xu

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

2011

Real-Time Volume Caustics with Image-Based Photon Tracing.

[BibT_eX]

[DOI]