Suvrit Sra

SIAM J. Optim., December, 2023

Riemannian Optimization via Frank-Wolfe Methods.

[BibT_eX]

[DOI]

Math. Program., May, 2023

Transformers Implement Functional Gradient Descent to Learn Non-Linear Functions In Context.

[BibT_eX]

[DOI]

Xiang Cheng

Yuxin Chen

CoRR, 2023

Linear attention is (maybe) all you need (to understand transformer optimization).

[BibT_eX]

[DOI]

CoRR, 2023

Invex Programs: First Order Algorithms and Their Convergence.

[BibT_eX]

[DOI]

Adarsh Barik

Jean Honorio

CoRR, 2023

How to escape sharp minima.

[BibT_eX]

[DOI]

CoRR, 2023

Transformers learn to implement preconditioned gradient descent for in-context learning.

[BibT_eX]

[DOI]

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

The Crucial Role of Normalization in Sharpness-Aware Minimization.

[BibT_eX]

[DOI]

Yan Dai

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

Can Direct Latent Model Learning Solve Linear Quadratic Gaussian Control?

[BibT_eX]

[DOI]

Proceedings of the Learning for Dynamics and Control Conference, 2023

On the Training Instability of Shuffling SGD with Batch Normalization.

[BibT_eX]

[DOI]

David Xing Wu

Proceedings of the International Conference on Machine Learning, 2023

Global optimality for Euclidean CCCP under Riemannian convexity.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Sign and Basis Invariant Networks for Spectral Graph Representation Learning.

[BibT_eX]

[DOI]

Derek Lim

Joshua David Robinson

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Toward Understanding State Representation Learning in MuZero: A Case Study in Linear Quadratic Gaussian Control.

[BibT_eX]

[DOI]

Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

2022

Computing Brascamp-Lieb Constants through the lens of Thompson Geometry.

[BibT_eX]

[DOI]

CoRR, 2022

On a class of geodesically convex optimization problems solved via Euclidean MM methods.

[BibT_eX]

[DOI]

CoRR, 2022

Minimax in Geodesic Metric Spaces: Sion's Theorem and Algorithms.

[BibT_eX]

[DOI]

Peiyuan Zhang

CoRR, 2022

Understanding Nesterov's Acceleration via Proximal Point Method.

[BibT_eX]

[DOI]

Proceedings of the 5th Symposium on Simplicity in Algorithms, 2022

CCCP is Frank-Wolfe in disguise.

[BibT_eX]

[DOI]

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

Efficient Sampling on Riemannian Manifolds via Langevin MCMC.

[BibT_eX]

[DOI]

Xiang Cheng

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

Time Varying Regression with Hidden Linear Dynamics.

[BibT_eX]

[DOI]

Proceedings of the Learning for Dynamics and Control Conference, 2022

Neural Network Weights Do Not Converge to Stationary Points: An Invariant Measure Perspective.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Beyond Worst-Case Analysis in Stochastic Approximation: Moment Estimation Improves Instance Complexity.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Understanding the unstable convergence of gradient descent.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Minibatch vs Local SGD with Shuffling: Tight Convergence Bounds and Beyond.

[BibT_eX]

[DOI]

Shashank Rajput

Proceedings of the Tenth International Conference on Learning Representations, 2022

Understanding Riemannian Acceleration via a Proximal Extragradient Framework.

[BibT_eX]

[DOI]

Jikai Jin

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

Max-Margin Contrastive Learning.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

A Riemannian Accelerated Proximal Extragradient Framework and its Implications.

[BibT_eX]

[DOI]

Jikai Jin

CoRR, 2021

On Convergence of Training Loss Without Reaching Stationary Points.

[BibT_eX]

[DOI]

CoRR, 2021

Can Single-Shuffle SGD be Better than Reshuffling SGD and GD?

[BibT_eX]

[DOI]

CoRR, 2021

Three Operator Splitting with Subgradients, Stochastic Gradients, and Adaptive Learning Rates.

[BibT_eX]

[DOI]

Alex Gu

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

Can contrastive learning avoid shortcut solutions?

[BibT_eX]

[DOI]

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

Three Operator Splitting with a Nonconvex Loss Function.

[BibT_eX]

[DOI]

Varun Mangalick

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

Provably Efficient Algorithms for Multi-Objective Competitive RL.

[BibT_eX]

[DOI]

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

Online Learning in Unknown Markov Games.

[BibT_eX]

[DOI]

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

Coping with Label Shift via Distributionally Robust Optimisation.

[BibT_eX]

[DOI]

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

Contrastive Learning with Hard Negative Samples.

[BibT_eX]

[DOI]

Joshua David Robinson

Ching-Yao Chuang

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

Open Problem: Can Single-Shuffle SGD be Better than Reshuffling SGD and GD?

[BibT_eX]

[DOI]

Proceedings of the Conference on Learning Theory, 2021

2020

An alternative to EM for Gaussian mixture models: batch and stochastic Riemannian optimization.

[BibT_eX]

[DOI]

Math. Program., 2020

An Interpretable Predictive Model of Vaccine Utilization for Tanzania.

[BibT_eX]

[DOI]

Frontiers Artif. Intell., 2020

Why do classifier accuracies show linear trends under distribution shift?

[BibT_eX]

[DOI]

Horia Mania

CoRR, 2020

Provably Efficient Online Agnostic Learning in Markov Games.

[BibT_eX]

[DOI]

CoRR, 2020

Stochastic Optimization with Non-stationary Noise.

[BibT_eX]

[DOI]

CoRR, 2020

On Tight Convergence Rates of Without-replacement SGD.

[BibT_eX]

[DOI]

CoRR, 2020

On Complexity of Finding Stationary Points of Nonsmooth Nonconvex Functions.

[BibT_eX]

[DOI]

CoRR, 2020

Why are Adaptive Methods Good for Attention Models?

[BibT_eX]

[DOI]

Sai Praneeth Karimireddy

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

Towards Minimax Optimal Reinforcement Learning in Factored Markov Decision Processes.

[BibT_eX]

[DOI]

Yi Tian

Jian Qian

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

SGD with shuffling: optimal rates without component convexity and large epoch requirements.

[BibT_eX]

[DOI]

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

Complexity of Finding Stationary Points of Nonconvex Nonsmooth Functions.

[BibT_eX]

[DOI]

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

Strength from Weakness: Fast Learning Using Weak Supervision.

[BibT_eX]

[DOI]

Joshua Robinson

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

Learning Adversarial Markov Decision Processes with Bandit Feedback and Unknown Transition.

[BibT_eX]

[DOI]

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

Why Gradient Clipping Accelerates Training: A Theoretical Justification for Adaptivity.

[BibT_eX]

[DOI]

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

From Nesterov's Estimate Sequence to Riemannian Acceleration.

[BibT_eX]

[DOI]

Proceedings of the Conference on Learning Theory, 2020

Geodesically-convex optimization for averaging partially observed covariance matrices.

[BibT_eX]

[DOI]

Proceedings of The 12th Asian Conference on Machine Learning, 2020

2019

Why ADAM Beats SGD for Attention Models.

[BibT_eX]

[DOI]

Sai Praneeth Karimireddy

CoRR, 2019

Metrics Induced by Quantum Jensen-Shannon-Renyí and Related Divergences.

[BibT_eX]

[DOI]

CoRR, 2019

Nonconvex stochastic optimization on manifolds via Riemannian Frank-Wolfe methods.

[BibT_eX]

[DOI]

CoRR, 2019

Analysis of Gradient Clipping and Adaptive Scaling with a Relaxed Smoothness Condition.

[BibT_eX]

[DOI]

CoRR, 2019

Are deep ResNets provably better than linear predictors?

[BibT_eX]

[DOI]

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

Small ReLU networks are powerful memorizers: a tight analysis of memorization capacity.

[BibT_eX]

[DOI]

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

Flexible Modeling of Diversity with Strongly Log-Concave Distributions.

[BibT_eX]

[DOI]

Joshua Robinson

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

Conditional Gradient Methods via Stochastic Path-Integrated Differential Estimator.

[BibT_eX]

[DOI]

Volkan Cevher

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

Escaping Saddle Points with Adaptive Gradient Methods.

[BibT_eX]

[DOI]

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

Random Shuffling Beats SGD after Finite Epochs.

[BibT_eX]

[DOI]

Jeff Z. HaoChen

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

Small nonlinearities in activation functions create bad local minima in neural networks.

[BibT_eX]

[DOI]

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

Efficiently testing local optimality and escaping saddles for ReLU networks.

[BibT_eX]

[DOI]

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

Acceleration in First Order Quasi-strongly Convex Optimization by ODE Discretization.

[BibT_eX]

[DOI]

Proceedings of the 58th IEEE Conference on Decision and Control, 2019

Learning Determinantal Point Processes by Corrective Negative Sampling.

[BibT_eX]

[DOI]

Mike Gartrell

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

2018

Modular Proximal Optimization for Multidimensional Total-Variation Regularization.

[BibT_eX]

[DOI]

Álvaro Barbero Jiménez

J. Mach. Learn. Res., 2018

Deep-RBF Networks Revisited: Robust Classification with Rejection.

[BibT_eX]

[DOI]

Pourya Habib Zadeh

CoRR, 2018

R-SPIDER: A Fast Riemannian Stochastic Optimization Algorithm with Curvature Independent Rate.

[BibT_eX]

[DOI]

CoRR, 2018

Finite sample expressive power of small-width ReLU networks.

[BibT_eX]

[DOI]

CoRR, 2018

Towards Riemannian Accelerated Gradient Methods.

[BibT_eX]

[DOI]

CoRR, 2018

Learning Determinantal Point Processes by Sampling Inferred Negatives.

[BibT_eX]

[DOI]

Mike Gartrell

CoRR, 2018

A Critical View of Global Optimality in Deep Learning.

[BibT_eX]

[DOI]

CoRR, 2018

Direct Runge-Kutta Discretization Achieves Acceleration.

[BibT_eX]

[DOI]

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

Exponentiated Strongly Rayleigh Distributions.

[BibT_eX]

[DOI]

Zelda E. Mariet

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

Global Optimality Conditions for Deep Neural Networks.

[BibT_eX]

[DOI]

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

Distributional Adversarial Networks.

[BibT_eX]

[DOI]

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

Non-Linear Temporal Subspace Representations for Activity Recognition.

[BibT_eX]

[DOI]

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

An Estimate Sequence for Geodesically Convex Optimization.

[BibT_eX]

[DOI]

Proceedings of the Conference On Learning Theory, 2018

On Geodesically Convex Formulations for the Brascamp-Lieb Constant.

[BibT_eX]

[DOI]

Nisheeth K. Vishnoi

Ozan Yildiz

Proceedings of the Approximation, 2018

A Generic Approach for Escaping Saddle points.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

Riemannian Dictionary Learning and Sparse Coding for Positive Definite Matrices.

[BibT_eX]

[DOI]

IEEE Trans. Neural Networks Learn. Syst., 2017

Frank-Wolfe methods for geodesically convex optimization with application to the matrix geometric mean.

[BibT_eX]

[DOI]

CoRR, 2017

Unsupervised robust nonparametric learning of hidden community properties.

[BibT_eX]

[DOI]

CoRR, 2017

Sequence Summarization Using Order-constrained Kernelized Feature Subspaces.

[BibT_eX]

[DOI]

Richard Hartley

CoRR, 2017

Elementary Symmetric Polynomials for Optimal Experimental Design.

[BibT_eX]

[DOI]

Zelda E. Mariet

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

Polynomial time algorithms for dual volume sampling.

[BibT_eX]

[DOI]

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

Combinatorial Topic Models using Small-Variance Asymptotics.

[BibT_eX]

[DOI]

Ke Jiang

Brian Kulis

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

2016

Entropic metric alignment for correspondence problems.

[BibT_eX]

[DOI]

ACM Trans. Graph., 2016

On inequalities for normalized Schur functions.

[BibT_eX]

[DOI]

Eur. J. Comb., 2016

Inference and mixture modeling with the Elliptical Gamma Distribution.

[BibT_eX]

[DOI]

Comput. Stat. Data Anal., 2016

Fast stochastic optimization on Riemannian manifolds.

[BibT_eX]

[DOI]

Sashank J. Reddi

CoRR, 2016

Fast Stochastic Methods for Nonsmooth Nonconvex Optimization.

[BibT_eX]

[DOI]

CoRR, 2016

Fast Incremental Method for Nonconvex Optimization.

[BibT_eX]

[DOI]

CoRR, 2016

Diversity Networks.

[BibT_eX]

[DOI]

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

Fast Sampling for Strongly Rayleigh Measures with Application to Determinantal Point Processes.

[BibT_eX]

[DOI]

CoRR, 2016

Riemannian SVRG: Fast Stochastic Optimization on Riemannian Manifolds.

[BibT_eX]

[DOI]

Sashank J. Reddi

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

Proximal Stochastic Methods for Nonsmooth Nonconvex Finite-Sum Optimization.

[BibT_eX]

[DOI]

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

Kronecker Determinantal Point Processes.

[BibT_eX]

[DOI]

Zelda E. Mariet

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

Fast Mixing Markov Chains for Strongly Rayleigh Measures, DPPs, and Constrained Sampling.

[BibT_eX]

[DOI]

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

Geometric Mean Metric Learning.

[BibT_eX]

[DOI]

Pourya Zadeh

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

Parallel and Distributed Block-Coordinate Frank-Wolfe Algorithms.

[BibT_eX]

[DOI]

Yu-Xiang Wang

Veeranjaneyulu Sadhanala

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

Stochastic Variance Reduction for Nonconvex Optimization.

[BibT_eX]

[DOI]

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

Gaussian quadrature for matrix inverse forms with applications.

[BibT_eX]

[DOI]

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

Fast DPP Sampling for Nystrom with Application to Kernel Methods.

[BibT_eX]

[DOI]

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

First-order Methods for Geodesically Convex Optimization.

[BibT_eX]

[DOI]

Proceedings of the 29th Conference on Learning Theory, 2016

Fast incremental method for smooth nonconvex optimization.

[BibT_eX]

[DOI]

Proceedings of the 55th IEEE Conference on Decision and Control, 2016

Stochastic Frank-Wolfe methods for nonconvex optimization.

[BibT_eX]

[DOI]

Proceedings of the 54th Annual Allerton Conference on Communication, 2016

AdaDelay: Delay Adaptive Distributed Stochastic Optimization.

[BibT_eX]

[DOI]

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

Efficient Sampling for k-Determinantal Point Processes.

[BibT_eX]

[DOI]

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

2015

Conic Geometric Optimization on the Manifold of Positive Definite Matrices.

[BibT_eX]

[DOI]

SIAM J. Optim., 2015

AdaDelay: Delay Adaptive Distributed Stochastic Convex Optimization.

[BibT_eX]

[DOI]

CoRR, 2015

Fixed-point algorithms for determinantal point processes.

[BibT_eX]

[DOI]

CoRR, 2015

Bounds on bilinear inverse forms via Gaussian quadrature with applications.

[BibT_eX]

[DOI]

CoRR, 2015

Convex Optimization for Parallel Energy Minimization.

[BibT_eX]

[DOI]

K. S. Sesh Kumar

Álvaro Barbero Jiménez

Francis R. Bach

CoRR, 2015

Manifold Optimization for Gaussian Mixture Models.

[BibT_eX]

[DOI]

CoRR, 2015

Large-scale randomized-coordinate descent methods with non-separable linear constraints.

[BibT_eX]

[DOI]

Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

On Variance Reduction in Stochastic Gradient Descent and its Asynchronous Variants.

[BibT_eX]

[DOI]

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

Matrix Manifold Optimization for Gaussian Mixtures.

[BibT_eX]

[DOI]

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

Fixed-point algorithms for learning determinantal point processes.

[BibT_eX]

[DOI]

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

Data modeling with the elliptical gamma distribution.

[BibT_eX]

[DOI]

Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014

Efficient Nearest Neighbors via Robust Sparse Hashing.

[BibT_eX]

[DOI]

Vassilios Morellas

IEEE Trans. Image Process., 2014

Fast Newton methods for the group fused lasso.

[BibT_eX]

[DOI]

Matt Wytock

Jeremy Z. Kolter

Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014

Efficient Structured Matrix Rank Minimization.

[BibT_eX]

[DOI]

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

Randomized Nonlinear Component Analysis.

[BibT_eX]

[DOI]

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

Towards an optimal stochastic alternating direction method of multipliers.

[BibT_eX]

[DOI]

Samaneh Azadi

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

Riemannian Sparse Coding for Positive Definite Matrices.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2014, 2014

Tractable Optimization in Machine Learning.

[BibT_eX]

[DOI]

Proceedings of the Tractability: Practical Approaches to Hard Problems, 2014

2013

Jensen-Bregman LogDet Divergence with Application to Efficient Similarity Search for Covariance Matrices.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2013

A non-monotonic method for large-scale non-negative least squares.

[BibT_eX]

[DOI]

Optim. Methods Softw., 2013

The multivariate Watson distribution: Maximum-likelihood estimation and other aspects.

[BibT_eX]

[DOI]

Dmitrii Karp

J. Multivar. Anal., 2013

Statistical estimation for optimization problems on graphs.

[BibT_eX]

[DOI]

Mikhail A. Langovoy

CoRR, 2013

Geometric optimisation on positive definite matrices for elliptically contoured distributions.

[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

Reflection methods for user-friendly submodular optimization.

[BibT_eX]

[DOI]

Francis R. Bach

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

2012

Fast projections onto mixed-norm balls with applications.

[BibT_eX]

[DOI]

Data Min. Knowl. Discov., 2012

A short note on parameter approximation for von Mises-Fisher distributions: and a fast implementation of I s (x).

[BibT_eX]

[DOI]

Comput. Stat., 2012

Scalable nonconvex inexact proximal splitting.

[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

A new metric on the manifold of kernel matrices with application to matrix geometric means.

[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

2011

Generalized Dictionary Learning for Symmetric Positive Definite Matrices with Application to Nearest Neighbor Retrieval.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

Fast Projections onto ℓ1, q -Norm Balls for Grouped Feature Selection.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

Fast Newton-type Methods for Total Variation Regularization.

[BibT_eX]

[DOI]

Álvaro Barbero Jiménez

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

Efficient similarity search for covariance matrices via the Jensen-Bregman LogDet Divergence.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Computer Vision, 2011

Denoising sparse noise via online dictionary learning.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2011

2010

Tackling Box-Constrained Optimization via a New Projected Quasi-Newton Approach.

[BibT_eX]

[DOI]

SIAM J. Sci. Comput., 2010

A scalable trust-region algorithm with application to mixed-norm regression.

[BibT_eX]

[DOI]

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

Multiframe blind deconvolution, super-resolution, and saturation correction via incremental EM.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Image Processing, 2010

Efficient filter flow for space-variant multiframe blind deconvolution.

[BibT_eX]

[DOI]

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

2009

Convex Perturbations for Scalable Semidefinite Programming.

[BibT_eX]

[DOI]

Brian Kulis

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

A Trivial Observation related to Sparse Recovery

[BibT_eX]

[DOI]

CoRR, 2009

Workshop summary: Numerical mathematics in machine learning.

[BibT_eX]

[DOI]

Matthias W. Seeger

John P. Cunningham

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

Approximation Algorithms for Tensor Clustering.

[BibT_eX]

[DOI]

Proceedings of the Algorithmic Learning Theory, 20th International Conference, 2009

2008

The Metric Nearness Problem.

[BibT_eX]

[DOI]

SIAM J. Matrix Anal. Appl., 2008

Fast Projection-Based Methods for the Least Squares Nonnegative Matrix Approximation Problem.

[BibT_eX]

[DOI]

Stat. Anal. Data Min., 2008

Approximation Algorithms for Bregman Co-clustering and Tensor Clustering

[BibT_eX]

[DOI]

CoRR, 2008

Block-Iterative Algorithms for Non-negative Matrix Approximation.

[BibT_eX]

[DOI]

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

2007

Fast Newton-type Methods for the Least Squares Nonnegative Matrix Approximation Problem.

[BibT_eX]

[DOI]

Proceedings of the Seventh SIAM International Conference on Data Mining, 2007

Information-theoretic metric learning.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning, 2007

2006

Incremental Aspect Models for Mining Document Streams.

[BibT_eX]

[DOI]

Arun C. Surendran

Proceedings of the Knowledge Discovery in Databases: PKDD 2006, 2006

Row-Action Methods for Compressed Sensing.

[BibT_eX]

[DOI]

Joel A. Tropp

Proceedings of the 2006 IEEE International Conference on Acoustics Speech and Signal Processing, 2006

Efficient Large Scale Linear Programming Support Vector Machines.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning: ECML 2006, 2006

2005

Clustering on the Unit Hypersphere using von Mises-Fisher Distributions.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2005

Generalized Nonnegative Matrix Approximations with Bregman Divergences.

[BibT_eX]

[DOI]

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

2004

Minimum Sum-Squared Residue Co-Clustering of Gene Expression Data.

[BibT_eX]

[DOI]

Proceedings of the Fourth SIAM International Conference on Data Mining, 2004

Triangle Fixing Algorithms for the Metric Nearness Problem.

[BibT_eX]

[DOI]