Thin Junction Trees. - Francis R. Bach; Michael I. Jordan (NIPS, 2001)

Learning Graphical Models with Mercer Kernels. - Francis R. Bach; Michael I. Jordan (NIPS, 2002)

Tree-dependent Component Analysis. - Francis R. Bach; Michael I. Jordan (UAI, 2002)

Kernel Independent Component Analysis. - Francis R. Bach; Michael I. Jordan (J. Mach. Learn. Res., 2002)

Learning Spectral Clustering. - Francis R. Bach; Michael I. Jordan (NIPS, 2003)

Kernel Dimensionality Reduction for Supervised Learning. - Kenji Fukumizu; Francis R. Bach; Michael I. Jordan (NIPS, 2003)

Beyond Independent Components: Trees and Clusters. - Francis R. Bach; Michael I. Jordan (J. Mach. Learn. Res., 2003)

Multiple kernel learning, conic duality, and the SMO algorithm. - Francis R. Bach; Gert R. G. Lanckriet; Michael I. Jordan (ICML, 2004)

Blind One-microphone Speech Separation: A Spectral Learning Approach. - Francis R. Bach; Michael I. Jordan (NIPS, 2004)

Computing regularization paths for learning multiple kernels. - Francis R. Bach; Romain Thibaux; Michael I. Jordan (NIPS, 2004)

Dimensionality Reduction for Supervised Learning with Reproducing Kernel Hilbert Spaces. - Kenji Fukumizu; Francis R. Bach; Michael I. Jordan (J. Mach. Learn. Res., 2004)

Learning graphical models for stationary time series. - Francis R. Bach; Michael I. Jordan (IEEE Trans. Signal Process., 2004)

On the Path to an Ideal ROC Curve: Considering Cost Asymmetry in Learning Classifiers. - Francis R. Bach; David Heckerman; Eric Horvitz (AISTATS, 2005)

Modèles de Markov cachés pour l'estimation de plusieurs fréquences fondamentales. - Michael I. Jordan; Francis R. Bach (EGC (Ateliers), 2005)

Discriminative training of hidden Markov models for multiple pitch tracking [speech processing examples]. - Francis R. Bach; Michael I. Jordan (ICASSP (5), 2005)

Predictive low-rank decomposition for kernel methods. - Francis R. Bach; Michael I. Jordan (ICML, 2005)

Statistical Convergence of Kernel CCA. - Kenji Fukumizu; Francis R. Bach; Arthur Gretton (NIPS, 2005)

Active learning for misspecified generalized linear models. - Francis R. Bach (NIPS, 2006)

SVM Speaker Verification using an Incomplete Cholesky Decomposition Sequence Kernel. - Jérôme Louradour; Khalid Daoudi; Francis R. Bach (Odyssey, 2006)

Low-rank matrix factorization with attributes - Jacob D. Abernethy; Francis R. Bach; Theodoros Evgeniou; Jean-Philippe Vert (CoRR, 2006)

Considering Cost Asymmetry in Learning Classifiers. - Francis R. Bach; David Heckerman; Eric Horvitz (J. Mach. Learn. Res., 2006)

Learning Spectral Clustering, With Application To Speech Separation. - Francis R. Bach; Michael I. Jordan (J. Mach. Learn. Res., 2006)

Image Classification with Segmentation Graph Kernels. - Zaïd Harchaoui; Francis R. Bach (CVPR, 2007)

More efficiency in multiple kernel learning. - Alain Rakotomamonjy; Francis R. Bach; Stéphane Canu; Yves Grandvalet (ICML, 2007)

Full regularization path for sparse principal component analysis. - Alexandre d'Aspremont; Francis R. Bach; Laurent El Ghaoui (ICML, 2007)

Segmentation of random textures by morphological and linear operators. - Aurélien Cord; Dominique Jeulin; Francis R. Bach (ISMM (1), 2007)

DIFFRAC: a discriminative and flexible framework for clustering. - Francis R. Bach; Zaïd Harchaoui (NIPS, 2007)

Testing for Homogeneity with Kernel Fisher Discriminant Analysis. - Zaïd Harchaoui; Francis R. Bach; Eric Moulines (NIPS, 2007)

Glycan classification with tree kernels. - Yoshihiro Yamanishi; Francis R. Bach; Jean-Philippe Vert (Bioinform., 2007)

Statistical Consistency of Kernel Canonical Correlation Analysis. - Kenji Fukumizu; Francis R. Bach; Arthur Gretton (J. Mach. Learn. Res., 2007)

Feature Space Mahalanobis Sequence Kernels: Application to SVM Speaker Verification. - Jérôme Louradour; Khalid Daoudi; Francis R. Bach (IEEE Trans. Speech Audio Process., 2007)

Discriminative learned dictionaries for local image analysis. - Julien Mairal; Francis R. Bach; Jean Ponce; Guillermo Sapiro; Andrew Zisserman (CVPR, 2008)

Discriminative Sparse Image Models for Class-Specific Edge Detection and Image Interpretation. - Julien Mairal; Marius Leordeanu; Francis R. Bach; Martial Hebert; Jean Ponce (ECCV (3), 2008)

A Path Following Algorithm for Graph Matching. - Mikhail Zaslavskiy; Francis R. Bach; Jean-Philippe Vert (ICISP, 2008)

Graph kernels between point clouds. - Francis R. Bach (ICML, 2008)

Bolasso: model consistent Lasso estimation through the bootstrap. - Francis R. Bach (ICML, 2008)

Sparse probabilistic projections. - Cédric Archambeau; Francis R. Bach (NIPS, 2008)

Exploring Large Feature Spaces with Hierarchical Multiple Kernel Learning. - Francis R. Bach (NIPS, 2008)

Kernel Change-point Analysis. - Zaïd Harchaoui; Francis R. Bach; Eric Moulines (NIPS, 2008)

Clustered Multi-Task Learning: A Convex Formulation. - Laurent Jacob; Francis R. Bach; Jean-Philippe Vert (NIPS, 2008)

Supervised Dictionary Learning. - Julien Mairal; Francis R. Bach; Jean Ponce; Guillermo Sapiro; Andrew Zisserman (NIPS, 2008)

Convex Sparse Matrix Factorizations - Francis R. Bach; Julien Mairal; Jean Ponce (CoRR, 2008)

Consistency of Trace Norm Minimization. - Francis R. Bach (J. Mach. Learn. Res., 2008)

Consistency of the Group Lasso and Multiple Kernel Learning. - Francis R. Bach (J. Mach. Learn. Res., 2008)

Optimal Solutions for Sparse Principal Component Analysis. - Alexandre d'Aspremont; Francis R. Bach; Laurent El Ghaoui (J. Mach. Learn. Res., 2008)

Automatic annotation of human actions in video. - Olivier Duchenne; Ivan Laptev; Josef Sivic; Francis R. Bach; Jean Ponce (ICCV, 2009)

Non-local sparse models for image restoration. - Julien Mairal; Francis R. Bach; Jean Ponce; Guillermo Sapiro; Andrew Zisserman (ICCV, 2009)

Online dictionary learning for sparse coding. - Julien Mairal; Francis R. Bach; Jean Ponce; Guillermo Sapiro (ICML, 2009)

Data-driven calibration of linear estimators with minimal penalties. - Sylvain Arlot; Francis R. Bach (NIPS, 2009)

Asymptotically Optimal Regularization in Smooth Parametric Models. - Percy Liang; Francis R. Bach; Guillaume Bouchard; Michael I. Jordan (NIPS, 2009)

Global alignment of protein-protein interaction networks by graph matching methods. - Mikhail Zaslavskiy; Francis R. Bach; Jean-Philippe Vert (Bioinform., 2009)

Model-Consistent Sparse Estimation through the Bootstrap - Francis R. Bach (CoRR, 2009)

High-Dimensional Non-Linear Variable Selection through Hierarchical Kernel Learning - Francis R. Bach (CoRR, 2009)

Self-concordant analysis for logistic regression - Francis R. Bach (CoRR, 2009)

A New Approach to Collaborative Filtering: Operator Estimation with Spectral Regularization. - Jacob D. Abernethy; Francis R. Bach; Theodoros Evgeniou; Jean-Philippe Vert (J. Mach. Learn. Res., 2009)

A Path Following Algorithm for the Graph Matching Problem. - Mikhail Zaslavskiy; Francis R. Bach; Jean-Philippe Vert (IEEE Trans. Pattern Anal. Mach. Intell., 2009)

Learning mid-level features for recognition. - Y-Lan Boureau; Francis R. Bach; Yann LeCun; Jean Ponce (CVPR, 2010)

Discriminative clustering for image co-segmentation. - Armand Joulin; Francis R. Bach; Jean Ponce (CVPR, 2010)

Proximal Methods for Sparse Hierarchical Dictionary Learning. - Rodolphe Jenatton; Julien Mairal; Guillaume Obozinski; Francis R. Bach (ICML, 2010)

Structured sparsity-inducing norms through submodular functions. - Francis R. Bach (NIPS, 2010)

Online Learning for Latent Dirichlet Allocation. - Matthew D. Hoffman; David M. Blei; Francis R. Bach (NIPS, 2010)

Efficient Optimization for Discriminative Latent Class Models. - Armand Joulin; Francis R. Bach; Jean Ponce (NIPS, 2010)

Network Flow Algorithms for Structured Sparsity. - Julien Mairal; Rodolphe Jenatton; Guillaume Obozinski; Francis R. Bach (NIPS, 2010)

Many-to-Many Graph Matching: A Continuous Relaxation Approach. - Mikhail Zaslavskiy; Francis R. Bach; Jean-Philippe Vert (ECML/PKDD (3), 2010)

Convex Relaxations for Subset Selection - Francis R. Bach; Selin Damla Ahipasaoglu; Alexandre d'Aspremont (CoRR, 2010)

Convex Analysis and Optimization with Submodular Functions: a Tutorial - Francis R. Bach (CoRR, 2010)

Structured Sparse Principal Component Analysis. - Rodolphe Jenatton; Guillaume Obozinski; Francis R. Bach (AISTATS, 2010)

Online Learning for Matrix Factorization and Sparse Coding. - Julien Mairal; Francis R. Bach; Jean Ponce; Guillermo Sapiro (J. Mach. Learn. Res., 2010)

Low-Rank Optimization on the Cone of Positive Semidefinite Matrices. - Michel Journée; Francis R. Bach; Pierre-Antoine Absil; Rodolphe Sepulchre (SIAM J. Optim., 2010)

Sparse image representation with epitomes. - Louise Benoît; Julien Mairal; Francis R. Bach; Jean Ponce (CVPR, 2011)

Itakura-Saito nonnegative matrix factorization with group sparsity. - Augustin Lefèvre; Francis R. Bach; Cédric Févotte (ICASSP, 2011)

Ask the locals: Multi-way local pooling for image recognition. - Y-Lan Boureau; Nicolas Le Roux; Francis R. Bach; Jean Ponce; Yann LeCun (ICCV, 2011)

Clusterpath: an Algorithm for Clustering using Convex Fusion Penalties. - Toby Hocking; Jean-Philippe Vert; Francis R. Bach; Armand Joulin (ICML, 2011)

Shaping Level Sets with Submodular Functions. - Francis R. Bach (NIPS, 2011)

Non-Asymptotic Analysis of Stochastic Approximation Algorithms for Machine Learning. - Francis R. Bach; Eric Moulines (NIPS, 2011)

Trace Lasso: a trace norm regularization for correlated designs. - Edouard Grave; Guillaume Obozinski; Francis R. Bach (NIPS, 2011)

Convergence Rates of Inexact Proximal-Gradient Methods for Convex Optimization. - Mark Schmidt 001; Nicolas Le Roux; Francis R. Bach (NIPS, 2011)

Multi-scale Mining of fMRI Data with Hierarchical Structured Sparsity. - Rodolphe Jenatton; Alexandre Gramfort; Vincent Michel; Guillaume Obozinski; Francis R. Bach; Bertrand Thirion (PRNI, 2011)

Online algorithms for nonnegative matrix factorization with the Itakura-Saito divergence. - Augustin Lefèvre; Francis R. Bach; Cédric Févotte (WASPAA, 2011)

Structured sparsity through convex optimization - Francis R. Bach; Rodolphe Jenatton; Julien Mairal; Guillaume Obozinski (CoRR, 2011)

Dictionary Learning for Deblurring and Digital Zoom - Florent Couzinie-Devy; Julien Mairal; Francis R. Bach; Jean Ponce (CoRR, 2011)

Learning Hierarchical and Topographic Dictionaries with Structured Sparsity - Julien Mairal; Rodolphe Jenatton; Guillaume Obozinski; Francis R. Bach (CoRR, 2011)

Structured Variable Selection with Sparsity-Inducing Norms. - Rodolphe Jenatton; Jean-Yves Audibert; Francis R. Bach (J. Mach. Learn. Res., 2011)

Proximal Methods for Hierarchical Sparse Coding. - Rodolphe Jenatton; Julien Mairal; Guillaume Obozinski; Francis R. Bach (J. Mach. Learn. Res., 2011)

Convex and Network Flow Optimization for Structured Sparsity. - Julien Mairal; Rodolphe Jenatton; Guillaume Obozinski; Francis R. Bach (J. Mach. Learn. Res., 2011)

Preface. - Alexandre d'Aspremont; Francis R. Bach; Inderjit S. Dhillon; Bin Yu 001 (Math. Program., 2011)

A Tensor-Based Algorithm for High-Order Graph Matching. - Olivier Duchenne; Francis R. Bach; In-So Kweon; Jean Ponce (IEEE Trans. Pattern Anal. Mach. Intell., 2011)

Multi-class cosegmentation. - Armand Joulin; Francis R. Bach; Jean Ponce (CVPR, 2012)

On the Equivalence between Herding and Conditional Gradient Algorithms. - Francis R. Bach; Simon Lacoste-Julien; Guillaume Obozinski (ICML, 2012)

A convex relaxation for weakly supervised classifiers. - Armand Joulin; Francis R. Bach (ICML, 2012)

Structured Sparsity and Convex Optimization. - Francis R. Bach (ICPRAM (1), 2012)

Semi-supervised NMF with Time-frequency Annotations for Single-channel Source Separation. - Augustin Lefèvre; Francis R. Bach; Cédric Févotte (ISMIR, 2012)

Multiple Operator-valued Kernel Learning. - Hachem Kadri; Alain Rakotomamonjy; Francis R. Bach; Philippe Preux (NIPS, 2012)

A Stochastic Gradient Method with an Exponential Convergence Rate for Finite Training Sets. - Nicolas Le Roux; Mark Schmidt 001; Francis R. Bach (NIPS, 2012)

A Stochastic Gradient Method with an Exponential Convergence Rate for Strongly-Convex Optimization with Finite Training Sets - Nicolas Le Roux; Mark Schmidt 001; Francis R. Bach (CoRR, 2012)

Convex Relaxation for Combinatorial Penalties - Guillaume Obozinski; Francis R. Bach (CoRR, 2012)

Local stability and robustness of sparse dictionary learning in the presence of noise - Rodolphe Jenatton; Rémi Gribonval; Francis R. Bach (CoRR, 2012)

A simpler approach to obtaining an O(1/t) convergence rate for the projected stochastic subgradient method - Simon Lacoste-Julien; Mark Schmidt 001; Francis R. Bach (CoRR, 2012)

Optimization with Sparsity-Inducing Penalties. - Francis R. Bach; Rodolphe Jenatton; Julien Mairal; Guillaume Obozinski (Found. Trends Mach. Learn., 2012)

Multi-task regression using minimal penalties. - Matthieu Solnon; Sylvain Arlot; Francis R. Bach (J. Mach. Learn. Res., 2012)

Task-Driven Dictionary Learning. - Julien Mairal; Francis R. Bach; Jean Ponce (IEEE Trans. Pattern Anal. Mach. Intell., 2012)

Multiscale Mining of fMRI Data with Hierarchical Structured Sparsity. - Rodolphe Jenatton; Alexandre Gramfort; Vincent Michel; Guillaume Obozinski; Evelyn Eger; Francis R. Bach; Bertrand Thirion (SIAM J. Imaging Sci., 2012)

Sharp analysis of low-rank kernel matrix approximations. - Francis R. Bach (COLT, 2013)

Hidden Markov tree models for semantic class induction. - Edouard Grave; Guillaume Obozinski; Francis R. Bach (CoNLL, 2013)

Structured Penalties for Log-Linear Language Models. - Anil Kumar Nelakanti; Cédric Archambeau; Julien Mairal; Francis R. Bach; Guillaume Bouchard (EMNLP, 2013)

Finding Actors and Actions in Movies. - Piotr Bojanowski; Francis R. Bach; Ivan Laptev; Jean Ponce; Cordelia Schmid; Josef Sivic (ICCV, 2013)

Learning Sparse Penalties for Change-point Detection using Max Margin Interval Regression. - Toby Hocking; Guillem Rigaill; Jean-Philippe Vert; Francis R. Bach (ICML (3), 2013)

Convex Relaxations for Learning Bounded-Treewidth Decomposable Graphs. - K. S. Sesh Kumar; Francis R. Bach (ICML (1), 2013)

Intersecting singularities for multi-structured estimation. - Emile Richard; Francis R. Bach; Jean-Philippe Vert (ICML (3), 2013)

Evaluating speech features with the minimal-pair ABX task: analysis of the classical MFC/PLP pipeline. - Thomas Schatz; Vijayaditya Peddinti; Francis R. Bach; Aren Jansen; Hynek Hermansky; Emmanuel Dupoux (INTERSPEECH, 2013)

Non-strongly-convex smooth stochastic approximation with convergence rate O(1/n). - Francis R. Bach; Eric Moulines (NIPS, 2013)

Reflection methods for user-friendly submodular optimization. - Stefanie Jegelka; Francis R. Bach; Suvrit Sra (NIPS, 2013)

Learning smoothing models of copy number profiles using breakpoint annotations. - Toby Dylan Hocking; Gudrun Schleiermacher; Isabelle Janoueix-Lerosey; Valentina Boeva; Julie Cappo; Olivier Delattre; Francis R. Bach; Jean-Philippe Vert (BMC Bioinform., 2013)

Convex relaxations of structured matrix factorizations. - Francis R. Bach (CoRR, 2013)

Domain adaptation for sequence labeling using hidden Markov models. - Edouard Grave; Guillaume Obozinski; Francis R. Bach (CoRR, 2013)

Maximizing submodular functions using probabilistic graphical models. - K. S. Sesh Kumar; Francis R. Bach (CoRR, 2013)

Local Component Analysis - Nicolas Le Roux; Francis R. Bach (ICLR (Poster), 2013)

Large-Margin Metric Learning for Partitioning Problems - Rémi Lajugie; Sylvain Arlot; Francis R. Bach (CoRR, 2013)

Learning with Submodular Functions: A Convex Optimization Perspective. - Francis R. Bach (Found. Trends Mach. Learn., 2013)

Low-Rank Optimization with Trace Norm Penalty. - Bamdev Mishra; Gilles Meyer; Francis R. Bach; Rodolphe Sepulchre (SIAM J. Optim., 2013)

Kernel-Based Methods for Hypothesis Testing: A Unified View. - Zaïd Harchaoui; Francis R. Bach; Olivier Cappé; Eric Moulines (IEEE Signal Process. Mag., 2013)

A Markovian approach to distributional semantics with application to semantic compositionality. - Edouard Grave; Guillaume Obozinski; Francis R. Bach (COLING, 2014)

Weakly Supervised Action Labeling in Videos under Ordering Constraints. - Piotr Bojanowski; Rémi Lajugie; Francis R. Bach; Ivan Laptev; Jean Ponce; Cordelia Schmid; Josef Sivic (ECCV (5), 2014)

Large-Margin Metric Learning for Constrained Partitioning Problems. - Rémi Lajugie; Francis R. Bach; Sylvain Arlot (ICML, 2014)

Evaluating speech features with the minimal-pair ABX task (II): resistance to noise. - Thomas Schatz; Vijayaditya Peddinti; Xuan-Nga Cao; Francis R. Bach; Hynek Hermansky; Emmanuel Dupoux (INTERSPEECH, 2014)

SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives. - Aaron Defazio; Francis R. Bach; Simon Lacoste-Julien (NIPS, 2014)

Metric Learning for Temporal Sequence Alignment. - Rémi Lajugie; Damien Garreau; Francis R. Bach; Sylvain Arlot (NIPS, 2014)

On the sample complexity of sparse dictionary learning. - Matthias Seibert; Martin Kleinsteuber; Rémi Gribonval; Rodolphe Jenatton; Francis R. Bach (SSP, 2014)

SegAnnDB: interactive Web-based genomic segmentation. - Toby Dylan Hocking; Valentina Boeva; Guillem Rigaill; Gudrun Schleiermacher; Isabelle Janoueix-Lerosey; Olivier Delattre; Wilfrid Richer; Franck Bourdeaut; Miyuki Suguro; Masao Seto; Francis R. Bach; Jean-Philippe Vert (Bioinform., 2014)

Constant Step Size Least-Mean-Square: Bias-Variance Trade-offs and Optimal Sampling Distributions. - Alexandre Défossez; Francis R. Bach (CoRR, 2014)

Sparse Modeling for Image and Vision Processing. - Julien Mairal; Francis R. Bach; Jean Ponce (Found. Trends Comput. Graph. Vis., 2014)

Adaptivity of averaged stochastic gradient descent to local strong convexity for logistic regression. - Francis R. Bach (J. Mach. Learn. Res., 2014)

Approximation bounds for sparse principal component analysis. - Alexandre d'Aspremont; Francis R. Bach; Laurent El Ghaoui (Math. Program., 2014)

Signal Processing for Big Data [From the Guest Editors]. - Georgios B. Giannakis; Francis R. Bach; Raphael Cendrillon; Michael W. Mahoney; Jennifer Neville (IEEE Signal Process. Mag., 2014)

Averaged Least-Mean-Squares: Bias-Variance Trade-offs and Optimal Sampling Distributions. - Alexandre Défossez; Francis R. Bach (AISTATS, 2015)

Sequential Kernel Herding: Frank-Wolfe Optimization for Particle Filtering. - Simon Lacoste-Julien; Fredrik Lindsten; Francis R. Bach (AISTATS, 2015)

From Averaging to Acceleration, There is Only a Step-size. - Nicolas Flammarion; Francis R. Bach (COLT, 2015)

An online EM algorithm in hidden (semi-)Markov models for audio segmentation and clustering. - Alberto Bietti; Francis R. Bach; Arshia Cont (ICASSP, 2015)

Weakly-Supervised Alignment of Video with Text. - Piotr Bojanowski; Rémi Lajugie; Edouard Grave; Francis R. Bach; Ivan Laptev; Jean Ponce; Cordelia Schmid (ICCV, 2015)

Rethinking LDA: Moment Matching for Discrete ICA. - Anastasia Podosinnikova; Francis R. Bach; Simon Lacoste-Julien (NIPS, 2015)

Spectral Norm Regularization of Orthonormal Representations for Graph Transduction. - Rakesh Shivanna; Bibaswan K. Chatterjee; Raman Sankaran; Chiranjib Bhattacharyya; Francis R. Bach (NIPS, 2015)

On the Equivalence between Quadrature Rules and Random Features. - Francis R. Bach (CoRR, 2015)

Submodular Functions: from Discrete to Continous Domains. - Francis R. Bach (CoRR, 2015)

Convex Optimization for Parallel Energy Minimization. - K. S. Sesh Kumar; Álvaro Barbero Jiménez; Stefanie Jegelka; Suvrit Sra; Francis R. Bach (CoRR, 2015)

Semidefinite and Spectral Relaxations for Multi-Label Classification. - Rémi Lajugie; Piotr Bojanowski; Sylvain Arlot; Francis R. Bach (CoRR, 2015)

Supervised Clustering in the Data Cube. - Vincent Roulet; Fajwel Fogel; Alexandre d'Aspremont; Francis R. Bach (CoRR, 2015)

Guest Editorial: Sparse Coding. - Julien Mairal; Michael Elad; Francis R. Bach (Int. J. Comput. Vis., 2015)

Duality Between Subgradient and Conditional Gradient Methods. - Francis R. Bach (SIAM J. Optim., 2015)

Convex Relaxations for Permutation Problems. - Fajwel Fogel; Rodolphe Jenatton; Francis R. Bach; Alexandre d'Aspremont (SIAM J. Matrix Anal. Appl., 2015)

Sparse and Spurious: Dictionary Learning With Noise and Outliers. - Rémi Gribonval; Rodolphe Jenatton; Francis R. Bach (IEEE Trans. Inf. Theory, 2015)

Sample Complexity of Dictionary Learning and Other Matrix Factorizations. - Rémi Gribonval; Rodolphe Jenatton; Francis R. Bach; Martin Kleinsteuber; Matthias Seibert (IEEE Trans. Inf. Theory, 2015)

Learning the Structure for Structured Sparsity. - Nino Shervashidze; Francis R. Bach (IEEE Trans. Signal Process., 2015)

Highly-Smooth Zero-th Order Online Optimization. - Francis R. Bach; Vianney Perchet (COLT, 2016)

A weakly-supervised discriminative model for audio-to-score alignment. - Rémi Lajugie; Piotr Bojanowski; Philippe Cuvillier; Sylvain Arlot; Francis R. Bach (ICASSP, 2016)

Beyond CCA: Moment Matching for Multi-View Models. - Anastasia Podosinnikova; Francis R. Bach; Simon Lacoste-Julien (ICML, 2016)

Exploiting Crowd Sourced Reviews to Explain Movie Recommendation. - Sara El Aouad; Christophe Dupuy; Renata Teixeira; Francis R. Bach; Christophe Diot (NETYS, 2016)

Stochastic Optimization for Large-scale Optimal Transport. - Aude Genevay; Marco Cuturi; Gabriel Peyré; Francis R. Bach (NIPS, 2016)

PAC-Bayesian Theory Meets Bayesian Inference. - Pascal Germain; Francis R. Bach; Alexandre Lacoste; Simon Lacoste-Julien (NIPS, 2016)

Stochastic Variance Reduction Methods for Saddle-Point Problems. - P. Balamurugan 001; Francis R. Bach (NIPS, 2016)

Parameter Learning for Log-supermodular Distributions. - Tatiana Shpakova; Francis R. Bach (NIPS, 2016)

Highly-Smooth Zero-th Order Online Optimization Vianney Perchet. - Francis R. Bach; Vianney Perchet (CoRR, 2016)

Identifying Groups of Strongly Correlated Variables through Smoothed Ordered Weighted L1-norms. - Raman Sankaran; Francis R. Bach; Chiranjib Bhattacharyya (AISTATS, 2017)

ASR Systems as Models of Phonetic Category Perception in Adults. - Thomas Schatz; Francis R. Bach; Emmanuel Dupoux (CogSci, 2017)

Stochastic Composite Least-Squares Regression with Convergence Rate $O(1/n)$. - Nicolas Flammarion; Francis R. Bach (COLT, 2017)

Kernel Square-Loss Exemplar Machines for Image Retrieval. - Rafael S. Rezende; Joaquin Zepeda; Jean Ponce; Francis R. Bach; Patrick Pérez (CVPR, 2017)

Primal-dual algorithms for non-negative matrix factorization with the Kullback-Leibler divergence. - Felipe Yanez; Francis R. Bach (ICASSP, 2017)

Optimal Algorithms for Smooth and Strongly Convex Distributed Optimization in Networks. - Kevin Scaman; Francis R. Bach; Sébastien Bubeck; Yin Tat Lee; Laurent Massoulié (ICML, 2017)

A Quantitative Measure of the Impact of Coarticulation on Phone Discriminability. - Thomas Schatz; Rory Turnbull; Francis R. Bach; Emmanuel Dupoux (INTERSPEECH, 2017)

Qualitative and Descriptive Topic Extraction from Movie Reviews Using LDA. - Christophe Dupuy; Francis R. Bach; Christophe Diot (MLDM, 2017)

On Structured Prediction Theory with Calibrated Convex Surrogate Losses. - Anton Osokin; Francis R. Bach; Simon Lacoste-Julien (NIPS, 2017)

Nonlinear Acceleration of Stochastic Algorithms. - Damien Scieur; Francis R. Bach; Alexandre d'Aspremont (NIPS, 2017)

Integration Methods and Optimization Algorithms. - Damien Scieur; Vincent Roulet; Francis R. Bach; Alexandre d'Aspremont (NIPS, 2017)

ILAB: An Interactive Labelling Strategy for Intrusion Detection. - Anaël Beaugnon; Pierre Chifflier; Francis R. Bach (RAID, 2017)

AdaBatch: Efficient Gradient Aggregation Rules for Sequential and Parallel Stochastic Gradient Methods. - Alexandre Défossez; Francis R. Bach (CoRR, 2017)

Breaking the Curse of Dimensionality with Convex Neural Networks. - Francis R. Bach (J. Mach. Learn. Res., 2017)

On the Equivalence between Kernel Quadrature Rules and Random Feature Expansions. - Francis R. Bach (J. Mach. Learn. Res., 2017)

Harder, Better, Faster, Stronger Convergence Rates for Least-Squares Regression. - Aymeric Dieuleveut; Nicolas Flammarion; Francis R. Bach (J. Mach. Learn. Res., 2017)

Online but Accurate Inference for Latent Variable Models with Local Gibbs Sampling. - Christophe Dupuy; Francis R. Bach (J. Mach. Learn. Res., 2017)

Robust Discriminative Clustering with Sparse Regularizers. - Nicolas Flammarion; Balamurugan Palaniappan; Francis R. Bach (J. Mach. Learn. Res., 2017)

Active-set Methods for Submodular Minimization Problems. - K. S. Sesh Kumar; Francis R. Bach (J. Mach. Learn. Res., 2017)

On the Consistency of Ordinal Regression Methods. - Fabian Pedregosa; Francis R. Bach; Alexandre Gramfort (J. Mach. Learn. Res., 2017)

Minimizing finite sums with the stochastic average gradient. - Mark Schmidt 001; Nicolas Le Roux; Francis R. Bach (Math. Program., 2017)

Erratum to: Minimizing finite sums with the stochastic average gradient. - Mark Schmidt 001; Nicolas Le Roux; Francis R. Bach (Math. Program., 2017)

End-to-End Active Learning for Computer Security Experts. - Anaël Beaugnon; Pierre Chifflier; Francis R. Bach (AAAI Workshops, 2018)

Learning Determinantal Point Processes in Sublinear Time. - Christophe Dupuy; Francis R. Bach (AISTATS, 2018)

Tracking the gradients using the Hessian: A new look at variance reducing stochastic methods. - Robert M. Gower; Nicolas Le Roux; Francis R. Bach (AISTATS, 2018)

Combinatorial Penalties: Which structures are preserved by convex relaxations? - Marwa El Halabi; Francis R. Bach; Volkan Cevher (AISTATS, 2018)

Convex Optimization over Intersection of Simple Sets: improved Convergence Rate Guarantees via an Exact Penalty Approach. - Achintya Kundu; Francis R. Bach; Chiranjib Bhattacharyya (AISTATS, 2018)

A Generic Approach for Escaping Saddle points. - Sashank J. Reddi; Manzil Zaheer; Suvrit Sra; Barnabás Póczos; Francis R. Bach; Ruslan Salakhutdinov; Alexander J. Smola (AISTATS, 2018)

Exponential Convergence of Testing Error for Stochastic Gradient Methods. - Loucas Pillaud-Vivien; Alessandro Rudi; Francis R. Bach (COLT, 2018)

Averaging Stochastic Gradient Descent on Riemannian Manifolds. - Nilesh Tripuraneni; Nicolas Flammarion; Francis R. Bach; Michael I. Jordan (COLT, 2018)

Consistent Dictionary Learning for Signal Declipping. - Lucas Rencker; Francis R. Bach; Wenwu Wang 001; Mark D. Plumbley (LVA/ICA, 2018)

Nonlinear Acceleration of CNNs. - Damien Scieur; Edouard Oyallon; Alexandre d'Aspremont; Francis R. Bach (ICLR (Workshop), 2018)

Efficient Algorithms for Non-convex Isotonic Regression through Submodular Optimization. - Francis R. Bach (NeurIPS, 2018)

On the Global Convergence of Gradient Descent for Over-parameterized Models using Optimal Transport. - Lénaïc Chizat; Francis R. Bach (NeurIPS, 2018)

SING: Symbol-to-Instrument Neural Generator. - Alexandre Défossez; Neil Zeghidour; Nicolas Usunier; Léon Bottou; Francis R. Bach (NeurIPS, 2018)

Relating Leverage Scores and Density using Regularized Christoffel Functions. - Edouard Pauwels; Francis R. Bach; Jean-Philippe Vert (NeurIPS, 2018)

Statistical Optimality of Stochastic Gradient Descent on Hard Learning Problems through Multiple Passes. - Loucas Pillaud-Vivien; Alessandro Rudi; Francis R. Bach (NeurIPS, 2018)

Optimal Algorithms for Non-Smooth Distributed Optimization in Networks. - Kevin Scaman; Francis R. Bach; Sébastien Bubeck; Laurent Massoulié; Yin Tat Lee (NeurIPS, 2018)

Rest-Katyusha: Exploiting the Solution's Structure via Scheduled Restart Schemes. - Junqi Tang; Mohammad Golbabaee; Francis R. Bach; Mike E. Davies 001 (NeurIPS, 2018)

Constant Step Size Stochastic Gradient Descent for Probabilistic Modeling. - Dmitry Babichev; Francis R. Bach (UAI, 2018)

Marginal Weighted Maximum Log-likelihood for Efficient Learning of Perturb-and-Map models. - Tatiana Shpakova; Francis R. Bach; Anton Osokin (UAI, 2018)

Gossip of Statistical Observations using Orthogonal Polynomials. - Raphaël Berthier; Francis R. Bach; Pierre Gaillard (CoRR, 2018)

Nonlinear Acceleration of Deep Neural Networks. - Damien Scieur; Edouard Oyallon; Alexandre d'Aspremont; Francis R. Bach (CoRR, 2018)

EM algorithms for ICA. - Pierre Ablin; Alexandre Gramfort; Jean-François Cardoso; Francis R. Bach (CoRR, 2018)

Approximating the Quadratic Transportation Metric in Near-Linear Time. - Jason M. Altschuler; Francis R. Bach; Alessandro Rudi; Jonathan Weed (CoRR, 2018)

A Note on Lazy Training in Supervised Differentiable Programming. - Lénaïc Chizat; Francis R. Bach (CoRR, 2018)

Stochastic algorithms with descent guarantees for ICA. - Pierre Ablin; Alexandre Gramfort; Jean-François Cardoso; Francis R. Bach (AISTATS, 2019)

Sample Complexity of Sinkhorn Divergences. - Aude Genevay; Lénaïc Chizat; Francis R. Bach; Marco Cuturi; Gabriel Peyré (AISTATS, 2019)

Accelerated Decentralized Optimization with Local Updates for Smooth and Strongly Convex Objectives. - Hadrien Hendrikx; Francis R. Bach; Laurent Massoulié (AISTATS, 2019)

Sharp Analysis of Learning with Discrete Losses. - Alex Nowak-Vila; Francis R. Bach; Alessandro Rudi (AISTATS, 2019)

Overcomplete Independent Component Analysis via SDP. - Anastasia Podosinnikova; Amelia Perry; Alexander S. Wein; Francis R. Bach; Alexandre d'Aspremont; David A. Sontag (AISTATS, 2019)

Fast and Faster Convergence of SGD for Over-Parameterized Models and an Accelerated Perceptron. - Sharan Vaswani; Francis R. Bach; Mark Schmidt 001 (AISTATS, 2019)

A Universal Algorithm for Variational Inequalities Adaptive to Smoothness and Noise. - Francis R. Bach; Kfir Y. Levy (COLT, 2019)

Beyond Least-Squares: Fast Rates for Regularized Empirical Risk Minimization through Self-Concordance. - Ulysse Marteau-Ferey; Dmitrii Ostrovskii; Francis R. Bach; Alessandro Rudi (COLT, 2019)

Stochastic first-order methods: non-asymptotic and computer-aided analyses via potential functions. - Adrien B. Taylor; Francis R. Bach (COLT, 2019)

Unsupervised Image Matching and Object Discovery as Optimization. - Huy V. Vo; Francis R. Bach; Minsu Cho; Kai Han 001; Yann LeCun; Patrick Pérez; Jean Ponce (CVPR, 2019)

Hyper-parameter Learning for Sparse Structured Probabilistic Models. - Tatiana Shpakova; Francis R. Bach; Mike E. Davies 001 (ICASSP, 2019)

Massively scalable Sinkhorn distances via the Nyström method. - Jason M. Altschuler; Francis R. Bach; Alessandro Rudi; Jonathan Niles-Weed (NeurIPS, 2019)

On Lazy Training in Differentiable Programming. - Lénaïc Chizat; Edouard Oyallon; Francis R. Bach (NeurIPS, 2019)

Localized Structured Prediction. - Carlo Ciliberto; Francis R. Bach; Alessandro Rudi (NeurIPS, 2019)

Implicit Regularization of Discrete Gradient Dynamics in Linear Neural Networks. - Gauthier Gidel; Francis R. Bach; Simon Lacoste-Julien (NeurIPS, 2019)

An Accelerated Decentralized Stochastic Proximal Algorithm for Finite Sums. - Hadrien Hendrikx; Francis R. Bach; Laurent Massoulié (NeurIPS, 2019)

Fast Decomposable Submodular Function Minimization using Constrained Total Variation. - Senanayak Sesh Kumar Karri; Francis R. Bach; Thomas Pock (NeurIPS, 2019)

UniXGrad: A Universal, Adaptive Algorithm with Optimal Guarantees for Constrained Optimization. - Ali Kavis; Kfir Y. Levy; Francis R. Bach; Volkan Cevher (NeurIPS, 2019)

Globally Convergent Newton Methods for Ill-conditioned Generalized Self-concordant Losses. - Ulysse Marteau-Ferey; Francis R. Bach; Alessandro Rudi (NeurIPS, 2019)

Partially Encrypted Deep Learning using Functional Encryption. - Théo Ryffel; David Pointcheval; Francis R. Bach; Edouard Dufour-Sans; Romain Gay (NeurIPS, 2019)

Towards closing the gap between the theory and practice of SVRG. - Othmane Sebbouh; Nidham Gazagnadou; Samy Jelassi; Francis R. Bach; Robert M. Gower (NeurIPS, 2019)

Asynchronous Accelerated Proximal Stochastic Gradient for Strongly Convex Distributed Finite Sums. - Hadrien Hendrikx; Francis R. Bach; Laurent Massoulié (CoRR, 2019)

A General Theory for Structured Prediction with Smooth Convex Surrogates. - Alex Nowak-Vila; Francis R. Bach; Alessandro Rudi (CoRR, 2019)

Efficient Primal-Dual Algorithms for Large-Scale Multiclass Classification. - Dmitry Babichev; Dmitrii Ostrovskii; Francis R. Bach (CoRR, 2019)

Implicit Regularization of Discrete Gradient Dynamics in Deep Linear Neural Networks. - Gauthier Gidel; Francis R. Bach; Simon Lacoste-Julien (CoRR, 2019)

Partially Encrypted Machine Learning using Functional Encryption. - Théo Ryffel; Edouard Dufour Sans; Romain Gay; Francis R. Bach; David Pointcheval (CoRR, 2019)

Max-Plus Matching Pursuit for Deterministic Markov Decision Processes. - Francis R. Bach (CoRR, 2019)

Demucs: Deep Extractor for Music Sources with extra unlabeled data remixed. - Alexandre Défossez; Nicolas Usunier; Léon Bottou; Francis R. Bach (CoRR, 2019)

Music Source Separation in the Waveform Domain. - Alexandre Défossez; Nicolas Usunier; Léon Bottou; Francis R. Bach (CoRR, 2019)

Optimal Convergence Rates for Convex Distributed Optimization in Networks. - Kevin Scaman; Francis R. Bach; Sébastien Bubeck; Yin Tat Lee; Laurent Massoulié (J. Mach. Learn. Res., 2019)

Submodular functions: from discrete to continuous domains. - Francis R. Bach (Math. Program., 2019)

Sparse Recovery and Dictionary Learning From Nonlinear Compressive Measurements. - Lucas Rencker; Francis R. Bach; Wenwu Wang 001; Mark D. Plumbley (IEEE Trans. Signal Process., 2019)

Statistical Estimation of the Poincaré constant and Application to Sampling Multimodal Distributions. - Loucas Pillaud-Vivien; Francis R. Bach; Tony Lelièvre; Alessandro Rudi; Gabriel Stoltz (AISTATS, 2020)

Implicit Bias of Gradient Descent for Wide Two-layer Neural Networks Trained with the Logistic Loss. - Lénaïc Chizat; Francis R. Bach (COLT, 2020)

Stochastic Optimization for Regularized Wasserstein Estimators. - Marin Ballu; Quentin Berthet; Francis R. Bach (ICML, 2020)

Structured Prediction with Partial Labelling through the Infimum Loss. - Vivien Cabannes; Alessandro Rudi; Francis R. Bach (ICML, 2020)

Statistically Preconditioned Accelerated Gradient Method for Distributed Optimization. - Hadrien Hendrikx; Lin Xiao; Sébastien Bubeck; Francis R. Bach; Laurent Massoulié (ICML, 2020)

Consistent Structured Prediction with Max-Min Margin Markov Networks. - Alex Nowak; Francis R. Bach; Alessandro Rudi (ICML, 2020)

Learning With Subquadratic Regularization : A Primal-Dual Approach. - Raman Sankaran; Francis R. Bach; Chiranjib Bhattacharyya (IJCAI, 2020)

Learning with Differentiable Pertubed Optimizers. - Quentin Berthet; Mathieu Blondel; Olivier Teboul; Marco Cuturi; Jean-Philippe Vert; Francis R. Bach (NeurIPS, 2020)

Tight Nonparametric Convergence Rates for Stochastic Gradient Descent under the Noiseless Linear Model. - Raphaël Berthier; Francis R. Bach; Pierre Gaillard (NeurIPS, 2020)

Batch normalization provably avoids ranks collapse for randomly initialised deep networks. - Hadi Daneshmand; Jonas Moritz Kohler; Francis R. Bach; Thomas Hofmann 001; Aurélien Lucchi (NeurIPS, 2020)

Dual-Free Stochastic Decentralized Optimization with Variance Reduction. - Hadrien Hendrikx; Francis R. Bach; Laurent Massoulié (NeurIPS, 2020)

Non-parametric Models for Non-negative Functions. - Ulysse Marteau-Ferey; Francis R. Bach; Alessandro Rudi (NeurIPS, 2020)

On the Effectiveness of Richardson Extrapolation in Machine Learning. - Francis R. Bach (CoRR, 2020)

Learning with Differentiable Perturbed Optimizers. - Quentin Berthet; Mathieu Blondel; Olivier Teboul; Marco Cuturi; Jean-Philippe Vert; Francis R. Bach (CoRR, 2020)

Safe Screening for the Generalized Conditional Gradient Method. - Yifan Sun 001; Francis R. Bach (CoRR, 2020)

Theoretical Understanding of Batch-normalization: A Markov Chain Perspective. - Hadi Daneshmand; Jonas Moritz Kohler; Francis R. Bach; Thomas Hofmann 001; Aurélien Lucchi (CoRR, 2020)

On the Convergence of Adam and Adagrad. - Alexandre Défossez; Léon Bottou; Francis R. Bach; Nicolas Usunier (CoRR, 2020)

ARIANN: Low-Interaction Privacy-Preserving Deep Learning via Function Secret Sharing. - Théo Ryffel; David Pointcheval; Francis R. Bach (CoRR, 2020)

Structured and Localized Image Restoration. - Thomas Eboli; Alex Nowak-Vila; Jian Sun 009; Francis R. Bach; Jean Ponce; Alessandro Rudi (CoRR, 2020)

Consistent Structured Prediction with Max-Min Margin Markov Networks. - Alex Nowak-Vila; Francis R. Bach; Alessandro Rudi (CoRR, 2020)

Max-Plus Linear Approximations for Deterministic Continuous-State Markov Decision Processes. - Eloïse Berthier; Francis R. Bach (IEEE Control. Syst. Lett., 2020)

Regularized nonlinear acceleration. - Damien Scieur; Alexandre d'Aspremont; Francis R. Bach (Math. Program., 2020)

Variance-Reduced Methods for Machine Learning. - Robert M. Gower; Mark Schmidt 001; Francis R. Bach; Peter Richtárik (Proc. IEEE, 2020)

Accelerated Gossip in Networks of Given Dimension Using Jacobi Polynomial Iterations. - Raphaël Berthier; Francis R. Bach; Pierre Gaillard (SIAM J. Math. Data Sci., 2020)

Explicit Regularization of Stochastic Gradient Methods through Duality. - Anant Raj; Francis R. Bach (AISTATS, 2021)

Fast Rates for Structured Prediction. - Vivien A. Cabannes; Francis R. Bach; Alessandro Rudi (COLT, 2021)

A Dimension-free Computational Upper-bound for Smooth Optimal Transport Estimation. - Adrien Vacher; Boris Muzellec; Alessandro Rudi; Francis R. Bach; François-Xavier Vialard (COLT, 2021)

Fast and Robust Stability Region Estimation for Nonlinear Dynamical Systems. - Eloïse Berthier; Justin Carpentier; Francis R. Bach (ECC, 2021)

Deep Equals Shallow for ReLU Networks in Kernel Regimes. - Alberto Bietti; Francis R. Bach (ICLR, 2021)

Disambiguation of Weak Supervision leading to Exponential Convergence rates. - Vivien A. Cabannes; Francis R. Bach; Alessandro Rudi (ICML, 2021)

Overcoming the curse of dimensionality with Laplacian regularization in semi-supervised learning. - Vivien Cabannes; Loucas Pillaud-Vivien; Francis R. Bach; Alessandro Rudi (NeurIPS, 2021)

Batch Normalization Orthogonalizes Representations in Deep Random Networks. - Hadi Daneshmand; Amir Joudaki; Francis R. Bach (NeurIPS, 2021)

Continuized Accelerations of Deterministic and Stochastic Gradient Descents, and of Gossip Algorithms. - Mathieu Even; Raphaël Berthier; Francis R. Bach; Nicolas Flammarion; Hadrien Hendrikx; Pierre Gaillard; Laurent Massoulié; Adrien B. Taylor (NeurIPS, 2021)

Disambiguation of weak supervision with exponential convergence rates. - Vivien Cabannes; Francis R. Bach; Alessandro Rudi (CoRR, 2021)

A Continuized View on Nesterov Acceleration. - Raphaël Berthier; Francis R. Bach; Nicolas Flammarion; Pierre Gaillard; Adrien B. Taylor (CoRR, 2021)

Max-Margin is Dead, Long Live Max-Margin! - Alex Nowak-Vila; Alessandro Rudi; Francis R. Bach (CoRR, 2021)

A Continuized View on Nesterov Acceleration for Stochastic Gradient Descent and Randomized Gossip. - Mathieu Even; Raphaël Berthier; Francis R. Bach; Nicolas Flammarion; Pierre Gaillard; Hadrien Hendrikx; Laurent Massoulié; Adrien B. Taylor (CoRR, 2021)

A Note on Optimizing Distributions using Kernel Mean Embeddings. - Boris Muzellec; Francis R. Bach; Alessandro Rudi (CoRR, 2021)

Gradient Descent on Infinitely Wide Neural Networks: Global Convergence and Generalization. - Francis R. Bach; Lenaïc Chizat (CoRR, 2021)

Learning PSD-valued functions using kernel sums-of-squares. - Boris Muzellec; Francis R. Bach; Alessandro Rudi (CoRR, 2021)

Near-optimal estimation of smooth transport maps with kernel sums-of-squares. - Boris Muzellec; Adrien Vacher; Francis R. Bach; François-Xavier Vialard; Alessandro Rudi (CoRR, 2021)

Stochastic quasi-gradient methods: variance reduction via Jacobian sketching. - Robert M. Gower; Peter Richtárik; Francis R. Bach (Math. Program., 2021)

An Optimal Algorithm for Decentralized Finite-Sum Optimization. - Hadrien Hendrikx; Francis R. Bach; Laurent Massoulié (SIAM J. Optim., 2021)

On the Effectiveness of Richardson Extrapolation in Data Science. - Francis R. Bach (SIAM J. Math. Data Sci., 2021)

Sampling from Arbitrary Functions via PSD Models. - Ulysse Marteau-Ferey; Francis R. Bach; Alessandro Rudi (AISTATS, 2022)

On the Consistency of Max-Margin Losses. - Alex Nowak; Alessandro Rudi; Francis R. Bach (AISTATS, 2022)

Infinite-Dimensional Sums-of-Squares for Optimal Control. - Eloïse Berthier; Justin Carpentier; Alessandro Rudi; Francis R. Bach (CDC, 2022)

The continuous-discrete variational Kalman filter (CD-VKF). - Marc Lambert; Silvère Bonnabel; Francis R. Bach (CDC, 2022)

Non-Convex Optimization with Certificates and Fast Rates Through Kernel Sums of Squares. - Blake E. Woodworth; Francis R. Bach; Alessandro Rudi (COLT, 2022)

Anticorrelated Noise Injection for Improved Generalization. - Antonio Orvieto; Hans Kersting; Frank Proske; Francis R. Bach; Aurélien Lucchi (ICML, 2022)

Convergence of Uncertainty Sampling for Active Learning. - Anant Raj; Francis R. Bach (ICML, 2022)

A Non-asymptotic Analysis of Non-parametric Temporal-Difference Learning. - Eloïse Berthier; Ziad Kobeissi; Francis R. Bach (NeurIPS, 2022)

Active Labeling: Streaming Stochastic Gradients. - Vivien Cabannes; Francis R. Bach; Vianney Perchet; Alessandro Rudi (NeurIPS, 2022)

Fast Stochastic Composite Minimization and an Accelerated Frank-Wolfe Algorithm under Parallelization. - Benjamin Dubois-Taine; Francis R. Bach; Quentin Berthet; Adrien B. Taylor (NeurIPS, 2022)

Variational inference via Wasserstein gradient flows. - Marc Lambert; Sinho Chewi; Francis R. Bach; Silvère Bonnabel; Philippe Rigollet (NeurIPS, 2022)

On the Theoretical Properties of Noise Correlation in Stochastic Optimization. - Aurélien Lucchi; Frank Proske; Antonio Orvieto; Francis R. Bach; Hans Kersting (NeurIPS, 2022)

Asynchronous SGD Beats Minibatch SGD Under Arbitrary Delays. - Konstantin Mishchenko; Francis R. Bach; Mathieu Even; Blake E. Woodworth (NeurIPS, 2022)

Differential Privacy Guarantees for Stochastic Gradient Langevin Dynamics. - Théo Ryffel; Francis R. Bach; David Pointcheval (CoRR, 2022)

On a Variance Reduction Correction of the Temporal Difference for Policy Evaluation in the Stochastic Continuous Setting. - Ziad Kobeissi; Francis R. Bach (CoRR, 2022)

Polynomial-time sparse measure recovery. - Hadi Daneshmand; Francis R. Bach (CoRR, 2022)

Entropy Maximization with Depth: A Variational Principle for Random Neural Networks. - Amir Joudaki; Hadi Daneshmand; Francis R. Bach (CoRR, 2022)

AriaNN: Low-Interaction Privacy-Preserving Deep Learning via Function Secret Sharing. - Théo Ryffel; Pierre Tholoniat; David Pointcheval; Francis R. Bach (Proc. Priv. Enhancing Technol., 2022)

The recursive variational Gaussian approximation (R-VGA). - Marc Lambert; Silvère Bonnabel; Francis R. Bach (Stat. Comput., 2022)

A Simple Convergence Proof of Adam and Adagrad. - Alexandre Défossez; Léon Bottou; Francis R. Bach; Nicolas Usunier (Trans. Mach. Learn. Res., 2022)

A note on approximate accelerated forward-backward methods with absolute and relative errors, and possibly strongly convex objectives. - Mathieu Barré; Adrien B. Taylor; Francis R. Bach (Open J. Math. Optim., 2022)

Screening for a Reweighted Penalized Conditional Gradient Method. - Yifan Sun 001; Francis R. Bach (Open J. Math. Optim., 2022)

Explicit Regularization in Overparametrized Models via Noise Injection. - Antonio Orvieto; Anant Raj; Hans Kersting; Francis R. Bach (AISTATS, 2023)

Regression as Classification: Influence of Task Formulation on Neural Network Features. - Lawrence Stewart; Francis R. Bach; Quentin Berthet; Jean-Philippe Vert (AISTATS, 2023)

Kernelized Diffusion Maps. - Loucas Pillaud-Vivien; Francis R. Bach (COLT, 2023)

Variational Gaussian Approximation of the Kushner Optimal Filter. - Marc Lambert; Silvère Bonnabel; Francis R. Bach (GSI (1), 2023)

On Bridging the Gap between Mean Field and Finite Width Deep Random Multilayer Perceptron with Batch Normalization. - Amir Joudaki; Hadi Daneshmand; Francis R. Bach (ICML, 2023)

Two Losses Are Better Than One: Faster Optimization Using a Cheaper Proxy. - Blake E. Woodworth; Konstantin Mishchenko; Francis R. Bach (ICML, 2023)

On the impact of activation and normalization in obtaining isometric embeddings at initialization. - Amir Joudaki; Hadi Daneshmand; Francis R. Bach (NeurIPS, 2023)

Regularization properties of adversarially-trained linear regression. - Antônio H. Ribeiro; Dave Zachariah; Francis R. Bach; Thomas B. Schön (NeurIPS, 2023)

Differentiable Clustering with Perturbed Spanning Forests. - Lawrence Stewart; Francis R. Bach; Felipe Llinares-López; Quentin Berthet (NeurIPS, 2023)

On the relationship between multivariate splines and infinitely-wide neural networks. - Francis R. Bach (CoRR, 2023)

Convergence Rates for Non-Log-Concave Sampling and Log-Partition Estimation. - David Holzmüller; Francis R. Bach (CoRR, 2023)

Universal Smoothed Score Functions for Generative Modeling. - Saeed Saremi; Rupesh Kumar Srivastava; Francis R. Bach (CoRR, 2023)

Theory and applications of the Sum-Of-Squares technique. - Francis R. Bach; Elisabetta Cornacchia; Luca Pesce; Giovanni Piccioli (CoRR, 2023)

Nonparametric Linear Feature Learning in Regression Through Regularisation. - Bertille Follain; Umut Simsekli; Francis Bach 001 (CoRR, 2023)

Variational Principles for Mirror Descent and Mirror Langevin Dynamics. - Belinda Tzen; Anant Raj; Maxim Raginsky; Francis R. Bach (IEEE Control. Syst. Lett., 2023)

Principled analyses and design of first-order methods with inexact proximal operators. - Mathieu Barré; Adrien B. Taylor; Francis R. Bach (Math. Program., 2023)

Information Theory With Kernel Methods. - Francis R. Bach (IEEE Trans. Inf. Theory, 2023)

The limited-memory recursive variational Gaussian approximation (L-RVGA). - Marc Lambert; Silvère Bonnabel; Francis R. Bach (Stat. Comput., 2023)

Exponential Convergence of Sum-of-Squares Hierarchies for Trigonometric Polynomials. - Francis R. Bach; Alessandro Rudi (SIAM J. Optim., 2023)

A Systematic Approach to Lyapunov Analyses of Continuous-Time Models in Convex Optimization. - Céline Moucer; Adrien B. Taylor; Francis R. Bach (SIAM J. Optim., 2023)

Classifier Calibration with ROC-Regularized Isotonic Regression. - Eugene Berta; Francis R. Bach; Michael I. Jordan (AISTATS, 2024)

The Galerkin method beats Graph-Based Approaches for Spectral Algorithms. - Vivien A Cabannnes; Francis Bach 001 (AISTATS, 2024)

On the Impact of Overparameterization on the Training of a Shallow Neural Network in High Dimensions. - Simon Martin 006; Francis R. Bach; Giulio Biroli (AISTATS, 2024)

Variational Dynamic Programming for Stochastic Optimal Control. - Marc Lambert; Francis R. Bach; Silvère Bonnabel (CDC, 2024)

Physics-informed machine learning as a kernel method. - Nathan Doumèche; Francis R. Bach; Gérard Biau; Claire Boyer (COLT, 2024)

Chain of Log-Concave Markov Chains. - Saeed Saremi; Ji Won Park; Francis R. Bach (ICLR, 2024)

Statistical and Geometrical properties of the Kernel Kullback-Leibler divergence. - Anna Korba; Francis R. Bach; Clémentine Chazal (NeurIPS, 2024)

Enhanced Feature Learning via Regularisation: Integrating Neural Networks and Kernel Methods. - Bertille Follain; Francis Bach 001 (CoRR, 2024)

Statistical and Geometrical properties of regularized Kernel Kullback-Leibler divergence. - Clémentine Chazal; Anna Korba; Francis R. Bach (CoRR, 2024)

Physics-informed kernel learning. - Nathan Doumèche; Francis R. Bach; Gérard Biau; Claire Boyer (CoRR, 2024)

Efficient Optimization Algorithms for Linear Adversarial Training. - Antônio H. Ribeiro; Thomas B. Schön; Dave Zahariah; Francis R. Bach (CoRR, 2024)

Low-Rank Plus Diagonal Approximations for Riccati-Like Matrix Differential Equations. - Silvère Bonnabel; Marc Lambert; Francis R. Bach (SIAM J. Matrix Anal. Appl., 2024)

Optimal Estimation of Smooth Transport Maps with Kernel SoS. - Adrien Vacher; Boris Muzellec; Francis R. Bach; François-Xavier Vialard; Alessandro Rudi (SIAM J. Math. Data Sci., 2024)

Second Order Conditions to Decompose Smooth Functions as Sums of Squares. - Ulysse Marteau-Ferey; Francis R. Bach; Alessandro Rudi (SIAM J. Optim., 2024)

High-Dimensional Analysis of Double Descent for Linear Regression with Random Projections. - Francis R. Bach (SIAM J. Math. Data Sci., 2024)

Variational Inference on the Boolean Hypercube with the Quantum Entropy. - Eliot Beyler; Francis Bach 001 (AISTATS, 2025)

Efficient Optimization Algorithms for Linear Adversarial Training. - Antônio H. Ribeiro; Thomas B. Schön; Dave Zachariah; Francis Bach 001 (AISTATS, 2025)

An uncertainty principle for Linear Recurrent Neural Networks. - Alexandre François; Antonio Orvieto; Francis R. Bach (COLT, 2025)

Optimizing Estimators of Squared Calibration Errors in Classification. - Sebastian Gregor Gruber; Francis R. Bach (Trans. Mach. Learn. Res., 2025)

The Surprising Agreement Between Convex Optimization Theory and Learning-Rate Scheduling for Large Model Training. - Fabian Schaipp; Alexander Hägele; Adrien B. Taylor; Umut Simsekli; Francis R. Bach (CoRR, 2025)

Rethinking Early Stopping: Refine, Then Calibrate. - Eugene Berta; David Holzmüller; Michael I. Jordan; Francis R. Bach (CoRR, 2025)

Sum-of-squares relaxations for polynomial min-max problems over simple sets. - Francis R. Bach (Math. Program., 2025)

Finding global minima via kernel approximations. - Alessandro Rudi; Ulysse Marteau-Ferey; Francis R. Bach (Math. Program., 2025)

Sampling Binary Data by Denoising through Score Functions. - Francis R. Bach; Saeed Saremi (CoRR, 2025)

Building Bridges between Regression, Clustering, and Classification. - Lawrence Stewart; Francis R. Bach; Quentin Berthet (CoRR, 2025)

Statistical Collusion by Collectives on Learning Platforms. - Etienne Gauthier; Francis R. Bach; Michael I. Jordan (CoRR, 2025)

Forecasting time series with constraints. - Nathan Doumèche; Francis R. Bach; Éloi Bedek; Gérard Biau; Claire Boyer; Yannig Goude (CoRR, 2025)

Spectral structure learning for clinical time series. - Ivan Lerner; Anita Burgun; Francis Bach 001 (CoRR, 2025)

Convergence of Shallow ReLU Networks on Weakly Interacting Data. - Léo Dana; Francis R. Bach; Loucas Pillaud-Vivien (CoRR, 2025)

Optimal Denoising in Score-Based Generative Models: The Role of Data Regularity. - Eliot Beyler; Francis Bach 001 (CoRR, 2025)

E-Values Expand the Scope of Conformal Prediction. - Etienne Gauthier; Francis R. Bach; Michael I. Jordan (CoRR, 2025)

Minimum Volume Conformal Sets for Multivariate Regression. - Sacha Braun; Liviu Aolaritei; Michael I. Jordan; Francis R. Bach (CoRR, 2025)

StablePCA: Learning Shared Representations across Multiple Sources via Minimax Optimization. - Zhenyu Wang; Molei Liu; Jing Lei; Francis Bach 001; Zijian Guo 003 (CoRR, 2025)

Backward Conformal Prediction. - Etienne Gauthier; Francis R. Bach; Michael I. Jordan (CoRR, 2025)

Scaling Laws for Gradient Descent and Sign Descent for Linear Bigram Models under Zipf's Law. - Frederik Kunstner; Francis Bach 001 (CoRR, 2025)

Sum-of-Squares Relaxations for Information Theory and Variational Inference. - Francis Bach 001 (Found. Comput. Math., 2025)

On the Effectiveness of the z-Transform Method in Quadratic Optimization. - Francis Bach 001 (CoRR, 2025)

Multivariate Conformal Prediction via Conformalized Gaussian Scoring. - Sacha Braun; Eugene Berta; Michael I. Jordan; Francis R. Bach (CoRR, 2025)

Convergence of Deterministic and Stochastic Diffusion-Model Samplers: A Simple Analysis in Wasserstein Distance. - Eliot Beyler; Francis R. Bach (CoRR, 2025)