Francis R. Bach

Affiliations:
  • École Normale Supérieure, Computer Science Department


According to our database1, Francis R. Bach authored at least 303 papers between 2001 and 2022.

Collaborative distances:

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Bibliography

2022
The recursive variational Gaussian approximation (R-VGA).
Stat. Comput., 2022

AriaNN: Low-Interaction Privacy-Preserving Deep Learning via Function Secret Sharing.
Proc. Priv. Enhancing Technol., 2022

Asynchronous SGD Beats Minibatch SGD Under Arbitrary Delays.
CoRR, 2022

Explicit Regularization in Overparametrized Models via Noise Injection.
CoRR, 2022

Variational inference via Wasserstein gradient flows.
CoRR, 2022

Active Labeling: Streaming Stochastic Gradients.
CoRR, 2022

Entropy Maximization with Depth: A Variational Principle for Random Neural Networks.
CoRR, 2022

A systematic approach to Lyapunov analyses of continuous-time models in convex optimization.
CoRR, 2022

Fast Stochastic Composite Minimization and an Accelerated Frank-Wolfe Algorithm under Parallelization.
CoRR, 2022

Polynomial-time sparse measure recovery.
CoRR, 2022

Information Theory with Kernel Methods.
CoRR, 2022

On a Variance Reduction Correction of the Temporal Difference for Policy Evaluation in the Stochastic Continuous Setting.
CoRR, 2022

Differential Privacy Guarantees for Stochastic Gradient Langevin Dynamics.
CoRR, 2022

Convergence of Uncertainty Sampling for Active Learning.
Proceedings of the International Conference on Machine Learning, 2022

Anticorrelated Noise Injection for Improved Generalization.
Proceedings of the International Conference on Machine Learning, 2022

Non-Convex Optimization with Certificates and Fast Rates Through Kernel Sums of Squares.
Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

On the Consistency of Max-Margin Losses.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Sampling from Arbitrary Functions via PSD Models.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
On the Effectiveness of Richardson Extrapolation in Data Science.
SIAM J. Math. Data Sci., 2021

An Optimal Algorithm for Decentralized Finite-Sum Optimization.
SIAM J. Optim., 2021

Stochastic quasi-gradient methods: variance reduction via Jacobian sketching.
Math. Program., 2021

Near-optimal estimation of smooth transport maps with kernel sums-of-squares.
CoRR, 2021

Learning PSD-valued functions using kernel sums-of-squares.
CoRR, 2021

Gradient Descent on Infinitely Wide Neural Networks: Global Convergence and Generalization.
CoRR, 2021

Screening for a Reweighted Penalized Conditional Gradient Method.
CoRR, 2021

A Note on Optimizing Distributions using Kernel Mean Embeddings.
CoRR, 2021

A Continuized View on Nesterov Acceleration for Stochastic Gradient Descent and Randomized Gossip.
CoRR, 2021

Max-Margin is Dead, Long Live Max-Margin!
CoRR, 2021

A Continuized View on Nesterov Acceleration.
CoRR, 2021

Disambiguation of weak supervision with exponential convergence rates.
CoRR, 2021

Continuized Accelerations of Deterministic and Stochastic Gradient Descents, and of Gossip Algorithms.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Batch Normalization Orthogonalizes Representations in Deep Random Networks.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Overcoming the curse of dimensionality with Laplacian regularization in semi-supervised learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Disambiguation of Weak Supervision leading to Exponential Convergence rates.
Proceedings of the 38th International Conference on Machine Learning, 2021

Deep Equals Shallow for ReLU Networks in Kernel Regimes.
Proceedings of the 9th International Conference on Learning Representations, 2021

Fast and Robust Stability Region Estimation for Nonlinear Dynamical Systems.
Proceedings of the 2021 European Control Conference, 2021

A Dimension-free Computational Upper-bound for Smooth Optimal Transport Estimation.
Proceedings of the Conference on Learning Theory, 2021

Fast Rates for Structured Prediction.
Proceedings of the Conference on Learning Theory, 2021

Explicit Regularization of Stochastic Gradient Methods through Duality.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Accelerated Gossip in Networks of Given Dimension Using Jacobi Polynomial Iterations.
SIAM J. Math. Data Sci., 2020

Variance-Reduced Methods for Machine Learning.
Proc. IEEE, 2020

Regularized nonlinear acceleration.
Math. Program., 2020

Max-Plus Linear Approximations for Deterministic Continuous-State Markov Decision Processes.
IEEE Control. Syst. Lett., 2020

Finding Global Minima via Kernel Approximations.
CoRR, 2020

Consistent Structured Prediction with Max-Min Margin Markov Networks.
CoRR, 2020

Structured and Localized Image Restoration.
CoRR, 2020

Principled Analyses and Design of First-Order Methods with Inexact Proximal Operators.
CoRR, 2020

ARIANN: Low-Interaction Privacy-Preserving Deep Learning via Function Secret Sharing.
CoRR, 2020

On the Convergence of Adam and Adagrad.
CoRR, 2020

Theoretical Understanding of Batch-normalization: A Markov Chain Perspective.
CoRR, 2020

Safe Screening for the Generalized Conditional Gradient Method.
CoRR, 2020

Learning with Differentiable Perturbed Optimizers.
CoRR, 2020

On the Effectiveness of Richardson Extrapolation in Machine Learning.
CoRR, 2020

Non-parametric Models for Non-negative Functions.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Dual-Free Stochastic Decentralized Optimization with Variance Reduction.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Batch normalization provably avoids ranks collapse for randomly initialised deep networks.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Tight Nonparametric Convergence Rates for Stochastic Gradient Descent under the Noiseless Linear Model.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning with Differentiable Pertubed Optimizers.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning With Subquadratic Regularization : A Primal-Dual Approach.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Consistent Structured Prediction with Max-Min Margin Markov Networks.
Proceedings of the 37th International Conference on Machine Learning, 2020

Statistically Preconditioned Accelerated Gradient Method for Distributed Optimization.
Proceedings of the 37th International Conference on Machine Learning, 2020

Structured Prediction with Partial Labelling through the Infimum Loss.
Proceedings of the 37th International Conference on Machine Learning, 2020

Stochastic Optimization for Regularized Wasserstein Estimators.
Proceedings of the 37th International Conference on Machine Learning, 2020

Implicit Bias of Gradient Descent for Wide Two-layer Neural Networks Trained with the Logistic Loss.
Proceedings of the Conference on Learning Theory, 2020

2019
Sparse Recovery and Dictionary Learning From Nonlinear Compressive Measurements.
IEEE Trans. Signal Process., 2019

Submodular functions: from discrete to continuous domains.
Math. Program., 2019

Optimal Convergence Rates for Convex Distributed Optimization in Networks.
J. Mach. Learn. Res., 2019

Music Source Separation in the Waveform Domain.
CoRR, 2019

Demucs: Deep Extractor for Music Sources with extra unlabeled data remixed.
CoRR, 2019

Max-Plus Matching Pursuit for Deterministic Markov Decision Processes.
CoRR, 2019

Partially Encrypted Machine Learning using Functional Encryption.
CoRR, 2019

Implicit Regularization of Discrete Gradient Dynamics in Deep Linear Neural Networks.
CoRR, 2019

Efficient Primal-Dual Algorithms for Large-Scale Multiclass Classification.
CoRR, 2019

A General Theory for Structured Prediction with Smooth Convex Surrogates.
CoRR, 2019

Asynchronous Accelerated Proximal Stochastic Gradient for Strongly Convex Distributed Finite Sums.
CoRR, 2019

Towards closing the gap between the theory and practice of SVRG.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Partially Encrypted Deep Learning using Functional Encryption.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Globally Convergent Newton Methods for Ill-conditioned Generalized Self-concordant Losses.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

UniXGrad: A Universal, Adaptive Algorithm with Optimal Guarantees for Constrained Optimization.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Fast Decomposable Submodular Function Minimization using Constrained Total Variation.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

An Accelerated Decentralized Stochastic Proximal Algorithm for Finite Sums.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Implicit Regularization of Discrete Gradient Dynamics in Linear Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

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

On Lazy Training in Differentiable Programming.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Massively scalable Sinkhorn distances via the Nyström method.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Hyper-parameter Learning for Sparse Structured Probabilistic Models.
Proceedings of the IEEE International Conference on Acoustics, 2019

Unsupervised Image Matching and Object Discovery as Optimization.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Stochastic first-order methods: non-asymptotic and computer-aided analyses via potential functions.
Proceedings of the Conference on Learning Theory, 2019

Beyond Least-Squares: Fast Rates for Regularized Empirical Risk Minimization through Self-Concordance.
Proceedings of the Conference on Learning Theory, 2019

A Universal Algorithm for Variational Inequalities Adaptive to Smoothness and Noise.
Proceedings of the Conference on Learning Theory, 2019

Fast and Faster Convergence of SGD for Over-Parameterized Models and an Accelerated Perceptron.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Overcomplete Independent Component Analysis via SDP.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Sharp Analysis of Learning with Discrete Losses.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Accelerated Decentralized Optimization with Local Updates for Smooth and Strongly Convex Objectives.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Sample Complexity of Sinkhorn Divergences.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Stochastic algorithms with descent guarantees for ICA.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
A Note on Lazy Training in Supervised Differentiable Programming.
CoRR, 2018

Approximating the Quadratic Transportation Metric in Near-Linear Time.
CoRR, 2018

EM algorithms for ICA.
CoRR, 2018

Nonlinear Acceleration of Deep Neural Networks.
CoRR, 2018

Gossip of Statistical Observations using Orthogonal Polynomials.
CoRR, 2018

Marginal Weighted Maximum Log-likelihood for Efficient Learning of Perturb-and-Map models.
Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Constant Step Size Stochastic Gradient Descent for Probabilistic Modeling.
Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Rest-Katyusha: Exploiting the Solution's Structure via Scheduled Restart Schemes.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Optimal Algorithms for Non-Smooth Distributed Optimization in Networks.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Statistical Optimality of Stochastic Gradient Descent on Hard Learning Problems through Multiple Passes.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Relating Leverage Scores and Density using Regularized Christoffel Functions.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

SING: Symbol-to-Instrument Neural Generator.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

On the Global Convergence of Gradient Descent for Over-parameterized Models using Optimal Transport.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Efficient Algorithms for Non-convex Isotonic Regression through Submodular Optimization.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Nonlinear Acceleration of CNNs.
Proceedings of the 6th International Conference on Learning Representations, 2018

Consistent Dictionary Learning for Signal Declipping.
Proceedings of the Latent Variable Analysis and Signal Separation, 2018

Averaging Stochastic Gradient Descent on Riemannian Manifolds.
Proceedings of the Conference On Learning Theory, 2018

Exponential Convergence of Testing Error for Stochastic Gradient Methods.
Proceedings of the Conference On Learning Theory, 2018

A Generic Approach for Escaping Saddle points.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Convex Optimization over Intersection of Simple Sets: improved Convergence Rate Guarantees via an Exact Penalty Approach.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Combinatorial Penalties: Which structures are preserved by convex relaxations?
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Tracking the gradients using the Hessian: A new look at variance reducing stochastic methods.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Learning Determinantal Point Processes in Sublinear Time.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

End-to-End Active Learning for Computer Security Experts.
Proceedings of the Workshops of the The Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Erratum to: Minimizing finite sums with the stochastic average gradient.
Math. Program., 2017

Minimizing finite sums with the stochastic average gradient.
Math. Program., 2017

On the Consistency of Ordinal Regression Methods.
J. Mach. Learn. Res., 2017

Active-set Methods for Submodular Minimization Problems.
J. Mach. Learn. Res., 2017

Robust Discriminative Clustering with Sparse Regularizers.
J. Mach. Learn. Res., 2017

Online but Accurate Inference for Latent Variable Models with Local Gibbs Sampling.
J. Mach. Learn. Res., 2017

Harder, Better, Faster, Stronger Convergence Rates for Least-Squares Regression.
J. Mach. Learn. Res., 2017

On the Equivalence between Kernel Quadrature Rules and Random Feature Expansions.
J. Mach. Learn. Res., 2017

Breaking the Curse of Dimensionality with Convex Neural Networks.
J. Mach. Learn. Res., 2017

AdaBatch: Efficient Gradient Aggregation Rules for Sequential and Parallel Stochastic Gradient Methods.
CoRR, 2017

ILAB: An Interactive Labelling Strategy for Intrusion Detection.
Proceedings of the Research in Attacks, Intrusions, and Defenses, 2017

Integration Methods and Optimization Algorithms.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Nonlinear Acceleration of Stochastic Algorithms.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

On Structured Prediction Theory with Calibrated Convex Surrogate Losses.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Qualitative and Descriptive Topic Extraction from Movie Reviews Using LDA.
Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2017

A Quantitative Measure of the Impact of Coarticulation on Phone Discriminability.
Proceedings of the Interspeech 2017, 2017

Optimal Algorithms for Smooth and Strongly Convex Distributed Optimization in Networks.
Proceedings of the 34th International Conference on Machine Learning, 2017

Primal-dual algorithms for non-negative matrix factorization with the Kullback-Leibler divergence.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Kernel Square-Loss Exemplar Machines for Image Retrieval.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

Stochastic Composite Least-Squares Regression with Convergence Rate $O(1/n)$.
Proceedings of the 30th Conference on Learning Theory, 2017

ASR Systems as Models of Phonetic Category Perception in Adults.
Proceedings of the 39th Annual Meeting of the Cognitive Science Society, 2017

Identifying Groups of Strongly Correlated Variables through Smoothed Ordered Weighted L<sub>1</sub>-norms.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016
Highly-Smooth Zero-th Order Online Optimization Vianney Perchet.
CoRR, 2016

Parameter Learning for Log-supermodular Distributions.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Stochastic Variance Reduction Methods for Saddle-Point Problems.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

PAC-Bayesian Theory Meets Bayesian Inference.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Stochastic Optimization for Large-scale Optimal Transport.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Exploiting Crowd Sourced Reviews to Explain Movie Recommendation.
Proceedings of the Networked Systems - 4th International Conference, 2016

Beyond CCA: Moment Matching for Multi-View Models.
Proceedings of the 33nd International Conference on Machine Learning, 2016

A weakly-supervised discriminative model for audio-to-score alignment.
Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

Highly-Smooth Zero-th Order Online Optimization.
Proceedings of the 29th Conference on Learning Theory, 2016

2015
Learning the Structure for Structured Sparsity.
IEEE Trans. Signal Process., 2015

Sample Complexity of Dictionary Learning and Other Matrix Factorizations.
IEEE Trans. Inf. Theory, 2015

Sparse and Spurious: Dictionary Learning With Noise and Outliers.
IEEE Trans. Inf. Theory, 2015

Convex Relaxations for Permutation Problems.
SIAM J. Matrix Anal. Appl., 2015

Duality Between Subgradient and Conditional Gradient Methods.
SIAM J. Optim., 2015

Guest Editorial: Sparse Coding.
Int. J. Comput. Vis., 2015

Supervised Clustering in the Data Cube.
CoRR, 2015

Semidefinite and Spectral Relaxations for Multi-Label Classification.
CoRR, 2015

Convex Optimization for Parallel Energy Minimization.
CoRR, 2015

Submodular Functions: from Discrete to Continous Domains.
CoRR, 2015

On the Equivalence between Quadrature Rules and Random Features.
CoRR, 2015

Spectral Norm Regularization of Orthonormal Representations for Graph Transduction.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Rethinking LDA: Moment Matching for Discrete ICA.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Weakly-Supervised Alignment of Video with Text.
Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

An online EM algorithm in hidden (semi-)Markov models for audio segmentation and clustering.
Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

From Averaging to Acceleration, There is Only a Step-size.
Proceedings of The 28th Conference on Learning Theory, 2015

Sequential Kernel Herding: Frank-Wolfe Optimization for Particle Filtering.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

Averaged Least-Mean-Squares: Bias-Variance Trade-offs and Optimal Sampling Distributions.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014
Signal Processing for Big Data [From the Guest Editors].
IEEE Signal Process. Mag., 2014

Approximation bounds for sparse principal component analysis.
Math. Program., 2014

Adaptivity of averaged stochastic gradient descent to local strong convexity for logistic regression.
J. Mach. Learn. Res., 2014

Sparse Modeling for Image and Vision Processing.
Found. Trends Comput. Graph. Vis., 2014

Constant Step Size Least-Mean-Square: Bias-Variance Trade-offs and Optimal Sampling Distributions.
CoRR, 2014

SegAnnDB: interactive Web-based genomic segmentation.
Bioinform., 2014

On the sample complexity of sparse dictionary learning.
Proceedings of the IEEE Workshop on Statistical Signal Processing, 2014

Metric Learning for Temporal Sequence Alignment.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Evaluating speech features with the minimal-pair ABX task (II): resistance to noise.
Proceedings of the INTERSPEECH 2014, 2014

Large-Margin Metric Learning for Constrained Partitioning Problems.
Proceedings of the 31th International Conference on Machine Learning, 2014

Weakly Supervised Action Labeling in Videos under Ordering Constraints.
Proceedings of the Computer Vision - ECCV 2014, 2014

A Markovian approach to distributional semantics with application to semantic compositionality.
Proceedings of the COLING 2014, 2014

2013
Kernel-Based Methods for Hypothesis Testing: A Unified View.
IEEE Signal Process. Mag., 2013

Low-Rank Optimization with Trace Norm Penalty.
SIAM J. Optim., 2013

Learning with Submodular Functions: A Convex Optimization Perspective.
Found. Trends Mach. Learn., 2013

Large-Margin Metric Learning for Partitioning Problems
CoRR, 2013

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

Maximizing submodular functions using probabilistic graphical models.
CoRR, 2013

Domain adaptation for sequence labeling using hidden Markov models.
CoRR, 2013

Convex relaxations of structured matrix factorizations.
CoRR, 2013

Learning smoothing models of copy number profiles using breakpoint annotations.
BMC Bioinform., 2013

Reflection methods for user-friendly submodular optimization.
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

Non-strongly-convex smooth stochastic approximation with convergence rate O(1/n).
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

Evaluating speech features with the minimal-pair ABX task: analysis of the classical MFC/PLP pipeline.
Proceedings of the INTERSPEECH 2013, 2013

Intersecting singularities for multi-structured estimation.
Proceedings of the 30th International Conference on Machine Learning, 2013

Convex Relaxations for Learning Bounded-Treewidth Decomposable Graphs.
Proceedings of the 30th International Conference on Machine Learning, 2013

Learning Sparse Penalties for Change-point Detection using Max Margin Interval Regression.
Proceedings of the 30th International Conference on Machine Learning, 2013

Finding Actors and Actions in Movies.
Proceedings of the IEEE International Conference on Computer Vision, 2013

Structured Penalties for Log-Linear Language Models.
Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing, 2013

Hidden Markov tree models for semantic class induction.
Proceedings of the Seventeenth Conference on Computational Natural Language Learning, 2013

Sharp analysis of low-rank kernel matrix approximations.
Proceedings of the COLT 2013, 2013

2012
Multiscale Mining of fMRI Data with Hierarchical Structured Sparsity.
SIAM J. Imaging Sci., 2012

Task-Driven Dictionary Learning.
IEEE Trans. Pattern Anal. Mach. Intell., 2012

Multi-task regression using minimal penalties.
J. Mach. Learn. Res., 2012

Optimization with Sparsity-Inducing Penalties.
Found. Trends Mach. Learn., 2012

A simpler approach to obtaining an O(1/t) convergence rate for the projected stochastic subgradient method
CoRR, 2012

Local stability and robustness of sparse dictionary learning in the presence of noise
CoRR, 2012

Convex Relaxation for Combinatorial Penalties
CoRR, 2012

A Stochastic Gradient Method with an Exponential Convergence Rate for Strongly-Convex Optimization with Finite Training Sets
CoRR, 2012

A Stochastic Gradient Method with an Exponential Convergence Rate for Finite Training Sets.
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

Multiple Operator-valued Kernel Learning.
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

Semi-supervised NMF with Time-frequency Annotations for Single-channel Source Separation.
Proceedings of the 13th International Society for Music Information Retrieval Conference, 2012

Structured Sparsity and Convex Optimization.
Proceedings of the ICPRAM 2012, 2012

A convex relaxation for weakly supervised classifiers.
Proceedings of the 29th International Conference on Machine Learning, 2012

On the Equivalence between Herding and Conditional Gradient Algorithms.
Proceedings of the 29th International Conference on Machine Learning, 2012

Multi-class cosegmentation.
Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012

2011
A Tensor-Based Algorithm for High-Order Graph Matching.
IEEE Trans. Pattern Anal. Mach. Intell., 2011

Preface.
Math. Program., 2011

Convex and Network Flow Optimization for Structured Sparsity.
J. Mach. Learn. Res., 2011

Proximal Methods for Hierarchical Sparse Coding.
J. Mach. Learn. Res., 2011

Structured Variable Selection with Sparsity-Inducing Norms.
J. Mach. Learn. Res., 2011

Learning Hierarchical and Topographic Dictionaries with Structured Sparsity
CoRR, 2011

Dictionary Learning for Deblurring and Digital Zoom
CoRR, 2011

Structured sparsity through convex optimization
CoRR, 2011

Online algorithms for nonnegative matrix factorization with the Itakura-Saito divergence.
Proceedings of the IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, 2011

Multi-scale Mining of fMRI Data with Hierarchical Structured Sparsity.
Proceedings of the 2011 International Workshop on Pattern Recognition in NeuroImaging, 2011

Convergence Rates of Inexact Proximal-Gradient Methods for Convex Optimization.
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

Trace Lasso: a trace norm regularization for correlated designs.
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

Non-Asymptotic Analysis of Stochastic Approximation Algorithms for Machine Learning.
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

Shaping Level Sets with Submodular Functions.
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

Clusterpath: an Algorithm for Clustering using Convex Fusion Penalties.
Proceedings of the 28th International Conference on Machine Learning, 2011

Ask the locals: Multi-way local pooling for image recognition.
Proceedings of the IEEE International Conference on Computer Vision, 2011

Itakura-Saito nonnegative matrix factorization with group sparsity.
Proceedings of the IEEE International Conference on Acoustics, 2011

Sparse image representation with epitomes.
Proceedings of the 24th IEEE Conference on Computer Vision and Pattern Recognition, 2011

2010
Low-Rank Optimization on the Cone of Positive Semidefinite Matrices.
SIAM J. Optim., 2010

Online Learning for Matrix Factorization and Sparse Coding.
J. Mach. Learn. Res., 2010

Structured Sparse Principal Component Analysis.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Convex Analysis and Optimization with Submodular Functions: a Tutorial
CoRR, 2010

Convex Relaxations for Subset Selection
CoRR, 2010

Many-to-Many Graph Matching: A Continuous Relaxation Approach.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

Network Flow Algorithms for Structured Sparsity.
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

Efficient Optimization for Discriminative Latent Class Models.
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

Online Learning for Latent Dirichlet Allocation.
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

Structured sparsity-inducing norms through submodular functions.
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

Proximal Methods for Sparse Hierarchical Dictionary Learning.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

Discriminative clustering for image co-segmentation.
Proceedings of the Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition, 2010

Learning mid-level features for recognition.
Proceedings of the Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition, 2010

2009
A Path Following Algorithm for the Graph Matching Problem.
IEEE Trans. Pattern Anal. Mach. Intell., 2009

A New Approach to Collaborative Filtering: Operator Estimation with Spectral Regularization.
J. Mach. Learn. Res., 2009

Self-concordant analysis for logistic regression
CoRR, 2009

High-Dimensional Non-Linear Variable Selection through Hierarchical Kernel Learning
CoRR, 2009

Model-Consistent Sparse Estimation through the Bootstrap
CoRR, 2009

Global alignment of protein-protein interaction networks by graph matching methods.
Bioinform., 2009

Asymptotically Optimal Regularization in Smooth Parametric Models.
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

Data-driven calibration of linear estimators with minimal penalties.
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

Online dictionary learning for sparse coding.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Non-local sparse models for image restoration.
Proceedings of the IEEE 12th International Conference on Computer Vision, ICCV 2009, Kyoto, Japan, September 27, 2009

Automatic annotation of human actions in video.
Proceedings of the IEEE 12th International Conference on Computer Vision, ICCV 2009, Kyoto, Japan, September 27, 2009

2008
Optimal Solutions for Sparse Principal Component Analysis.
J. Mach. Learn. Res., 2008

Consistency of the Group Lasso and Multiple Kernel Learning.
J. Mach. Learn. Res., 2008

Consistency of Trace Norm Minimization.
J. Mach. Learn. Res., 2008

Convex Sparse Matrix Factorizations
CoRR, 2008

Supervised Dictionary Learning.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Clustered Multi-Task Learning: A Convex Formulation.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Kernel Change-point Analysis.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Exploring Large Feature Spaces with Hierarchical Multiple Kernel Learning.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Sparse probabilistic projections.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Bolasso: model consistent Lasso estimation through the bootstrap.
Proceedings of the Machine Learning, 2008

Graph kernels between point clouds.
Proceedings of the Machine Learning, 2008

A Path Following Algorithm for Graph Matching.
Proceedings of the Image and Signal Processing - 3rd International Conference, 2008

Discriminative Sparse Image Models for Class-Specific Edge Detection and Image Interpretation.
Proceedings of the Computer Vision, 2008

Discriminative learned dictionaries for local image analysis.
Proceedings of the 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2008), 2008

2007
Feature Space Mahalanobis Sequence Kernels: Application to SVM Speaker Verification.
IEEE Trans. Speech Audio Process., 2007

Statistical Consistency of Kernel Canonical Correlation Analysis.
J. Mach. Learn. Res., 2007

Glycan classification with tree kernels.
Bioinform., 2007

Testing for Homogeneity with Kernel Fisher Discriminant Analysis.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

DIFFRAC: a discriminative and flexible framework for clustering.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Segmentation of random textures by morphological and linear operators.
Proceedings of the 8th ISMM 2007: Rio de Janeiro, Brazil - Volume 1, 2007

Full regularization path for sparse principal component analysis.
Proceedings of the Machine Learning, 2007

More efficiency in multiple kernel learning.
Proceedings of the Machine Learning, 2007

Image Classification with Segmentation Graph Kernels.
Proceedings of the 2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2007), 2007

2006
Learning Spectral Clustering, With Application To Speech Separation.
J. Mach. Learn. Res., 2006

Considering Cost Asymmetry in Learning Classifiers.
J. Mach. Learn. Res., 2006

Low-rank matrix factorization with attributes
CoRR, 2006

SVM Speaker Verification using an Incomplete Cholesky Decomposition Sequence Kernel.
Proceedings of the Odyssey 2006, 2006

Active learning for misspecified generalized linear models.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

2005
Statistical Convergence of Kernel CCA.
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

Predictive low-rank decomposition for kernel methods.
Proceedings of the Machine Learning, 2005

Discriminative training of hidden Markov models for multiple pitch tracking [speech processing examples].
Proceedings of the 2005 IEEE International Conference on Acoustics, 2005

Modèles de Markov cachés pour l'estimation de plusieurs fréquences fondamentales.
Proceedings of the Extraction des connaissances : Etat et perspectives (Ateliers de la conférence EGC'2005), 2005

On the Path to an Ideal ROC Curve: Considering Cost Asymmetry in Learning Classifiers.
Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, 2005

2004
Learning graphical models for stationary time series.
IEEE Trans. Signal Process., 2004

Dimensionality Reduction for Supervised Learning with Reproducing Kernel Hilbert Spaces.
J. Mach. Learn. Res., 2004

Computing regularization paths for learning multiple kernels.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Blind One-microphone Speech Separation: A Spectral Learning Approach.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Multiple kernel learning, conic duality, and the SMO algorithm.
Proceedings of the Machine Learning, 2004

2003
Beyond Independent Components: Trees and Clusters.
J. Mach. Learn. Res., 2003

Kernel Dimensionality Reduction for Supervised Learning.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Learning Spectral Clustering.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

2002
Kernel Independent Component Analysis.
J. Mach. Learn. Res., 2002

Tree-dependent Component Analysis.
Proceedings of the UAI '02, 2002

Learning Graphical Models with Mercer Kernels.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

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


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