ML Anthology

Bach, Francis

111 publications

COLT 2025 An Uncertainty Principle for Linear Recurrent Neural Networks Alexandre François, Antonio Orvieto, Francis Bach
NeurIPS 2025 Backward Conformal Prediction Etienne Gauthier, Francis Bach, Michael I. Jordan
JMLR 2025 Convergence Rates for Non-Log-Concave Sampling and Log-Partition Estimation David Holzmüller, Francis Bach
NeurIPS 2025 Convergence of the Gradient Flow for Shallow ReLU Networks on Weakly Interacting Data Léo Dana, Loucas Pillaud-Vivien, Francis Bach
AISTATS 2025 Efficient Optimization Algorithms for Linear Adversarial Training Antonio H. Ribeiro, Thomas B. Schön, Dave Zachariah, Francis Bach
JMLR 2025 Enhanced Feature Learning via Regularisation: Integrating Neural Networks and Kernel Methods Bertille Follain, Francis Bach
NeurIPS 2025 Kernel Learning with Adversarial Features: Numerical Efficiency and Adaptive Regularization Antonio H. Ribeiro, David Vävinggren, Dave Zachariah, Thomas B. Schön, Francis Bach
JMLR 2025 Physics-Informed Kernel Learning Nathan Doumèche, Francis Bach, Gérard Biau, Claire Boyer
ICML 2025 Sampling Binary Data by Denoising Through Score Functions Francis Bach, Saeed Saremi
NeurIPS 2025 Scaling Laws for Gradient Descent and Sign Descent for Linear Bigram Models Under Zipf’s Law Frederik Kunstner, Francis Bach
ICML 2025 Statistical Collusion by Collectives on Learning Platforms Etienne Gauthier, Francis Bach, Michael I. Jordan
ICML 2025 The Surprising Agreement Between Convex Optimization Theory and Learning-Rate Scheduling for Large Model Training Fabian Schaipp, Alexander Hägele, Adrien Taylor, Umut Simsekli, Francis Bach
AISTATS 2025 Variational Inference on the Boolean Hypercube with the Quantum Entropy Eliot Beyler, Francis Bach
ICLR 2024 Chain of Log-Concave Markov Chains Saeed Saremi, Ji Won Park, Francis Bach
AISTATS 2024 Classifier Calibration with ROC-Regularized Isotonic Regression Eugène Berta, Francis Bach, Michael Jordan
AISTATS 2024 On the Impact of Overparameterization on the Training of a Shallow Neural Network in High Dimensions Simon Martin, Francis Bach, Giulio Biroli
COLT 2024 Physics-Informed Machine Learning as a Kernel Method Nathan Doumèche, Francis Bach, Gérard Biau, Claire Boyer
NeurIPSW 2024 Spectral Structure Learning for Clinical Time Series Ivan Lerner, Francis Bach, Anita Burgun
NeurIPS 2024 Statistical and Geometrical Properties of the Kernel Kullback-Leibler Divergence Clémentine Chazal, Anna Korba, Francis Bach
AISTATS 2024 The Galerkin Method Beats Graph-Based Approaches for Spectral Algorithms Vivien A. Cabannes, Francis Bach
ICMLW 2023 Differentiable Clustering and Partial Fenchel-Young Losses Lawrence Stewart, Francis Bach, Felipe Llinares-López, Quentin Berthet
AISTATS 2023 Explicit Regularization in Overparametrized Models via Noise Injection Antonio Orvieto, Anant Raj, Hans Kersting, Francis Bach
COLT 2023 Kernelized Diffusion Maps Loucas Pillaud-Vivien, Francis Bach
ICML 2023 On Bridging the Gap Between Mean Field and Finite Width Deep Random Multilayer Perceptron with Batch Normalization Amir Joudaki, Hadi Daneshmand, Francis Bach
AISTATS 2023 Regression as Classification: Influence of Task Formulation on Neural Network Features Lawrence Stewart, Francis Bach, Quentin Berthet, Jean-Philippe Vert
ICML 2023 Two Losses Are Better than One: Faster Optimization Using a Cheaper Proxy Blake Woodworth, Konstantin Mishchenko, Francis Bach
AISTATS 2022 On the Consistency of Max-Margin Losses Alex Nowak, Alessandro Rudi, Francis Bach
AISTATS 2022 Sampling from Arbitrary Functions via PSD Models Ulysse Marteau-Ferey, Francis Bach, Alessandro Rudi
TMLR 2022 A Simple Convergence Proof of Adam and AdaGrad Alexandre Défossez, Leon Bottou, Francis Bach, Nicolas Usunier
ICML 2022 Anticorrelated Noise Injection for Improved Generalization Antonio Orvieto, Hans Kersting, Frank Proske, Francis Bach, Aurelien Lucchi
ICML 2022 Convergence of Uncertainty Sampling for Active Learning Anant Raj, Francis Bach
COLT 2022 Non-Convex Optimization with Certificates and Fast Rates Through Kernel Sums of Squares Blake Woodworth, Francis Bach, Alessandro Rudi
AISTATS 2021 Explicit Regularization of Stochastic Gradient Methods Through Duality Anant Raj, Francis Bach
COLT 2021 A Dimension-Free Computational Upper-Bound for Smooth Optimal Transport Estimation Adrien Vacher, Boris Muzellec, Alessandro Rudi, Francis Bach, Francois-Xavier Vialard
ICLR 2021 Deep Equals Shallow for ReLU Networks in Kernel Regimes Alberto Bietti, Francis Bach
ICML 2021 Disambiguation of Weak Supervision Leading to Exponential Convergence Rates Vivien A Cabannnes, Francis Bach, Alessandro Rudi
COLT 2021 Fast Rates for Structured Prediction Vivien A Cabannes, Francis Bach, Alessandro Rudi
ICML 2020 Consistent Structured Prediction with Max-Min Margin Markov Networks Alex Nowak, Francis Bach, Alessandro Rudi
COLT 2020 Implicit Bias of Gradient Descent for Wide Two-Layer Neural Networks Trained with the Logistic Loss Lénaïc Chizat, Francis Bach
AISTATS 2020 Statistical Estimation of the Poincaré Constant and Application to Sampling Multimodal Distributions Loucas Pillaud-Vivien, Francis Bach, Tony Lelièvre, Alessandro Rudi, Gabriel Stoltz
ICML 2020 Statistically Preconditioned Accelerated Gradient Method for Distributed Optimization Hadrien Hendrikx, Lin Xiao, Sebastien Bubeck, Francis Bach, Laurent Massoulie
ICML 2020 Stochastic Optimization for Regularized Wasserstein Estimators Marin Ballu, Quentin Berthet, Francis Bach
ICML 2020 Structured Prediction with Partial Labelling Through the Infimum Loss Vivien Cabannnes, Alessandro Rudi, Francis Bach
COLT 2019 A Universal Algorithm for Variational Inequalities Adaptive to Smoothness and Noise Francis Bach, Kfir Y Levy
AISTATS 2019 Accelerated Decentralized Optimization with Local Updates for Smooth and Strongly Convex Objectives Hadrien Hendrikx, Francis Bach, Laurent Massoulie
NeurIPS 2019 An Accelerated Decentralized Stochastic Proximal Algorithm for Finite Sums Hadrien Hendrikx, Francis Bach, Laurent Massoulié
COLT 2019 Beyond Least-Squares: Fast Rates for Regularized Empirical Risk Minimization Through Self-Concordance Ulysse Marteau-Ferey, Dmitrii Ostrovskii, Francis Bach, Alessandro Rudi
NeurIPS 2019 Fast Decomposable Submodular Function Minimization Using Constrained Total Variation Senanayak Sesh Kumar Karri, Francis Bach, Thomas Pock
AISTATS 2019 Fast and Faster Convergence of SGD for Over-Parameterized Models and an Accelerated Perceptron Sharan Vaswani, Francis Bach, Mark Schmidt
NeurIPS 2019 Globally Convergent Newton Methods for Ill-Conditioned Generalized Self-Concordant Losses Ulysse Marteau-Ferey, Francis Bach, Alessandro Rudi
NeurIPS 2019 Implicit Regularization of Discrete Gradient Dynamics in Linear Neural Networks Gauthier Gidel, Francis Bach, Simon Lacoste-Julien
NeurIPS 2019 Localized Structured Prediction Carlo Ciliberto, Francis Bach, Alessandro Rudi
NeurIPS 2019 Massively Scalable Sinkhorn Distances via the Nyström Method Jason Altschuler, Francis Bach, Alessandro Rudi, Jonathan Niles-Weed
NeurIPS 2019 On Lazy Training in Differentiable Programming Lénaïc Chizat, Edouard Oyallon, Francis Bach
JMLR 2019 Optimal Convergence Rates for Convex Distributed Optimization in Networks Kevin Scaman, Francis Bach, Sébastien Bubeck, Yin Tat Lee, Laurent Massoulié
AISTATS 2019 Overcomplete Independent Component Analysis via SDP Anastasia Podosinnikova, Amelia Perry, Alexander S. Wein, Francis Bach, Alexandre d’Aspremont, David Sontag
NeurIPS 2019 Partially Encrypted Deep Learning Using Functional Encryption Théo Ryffel, David Pointcheval, Francis Bach, Edouard Dufour-Sans, Romain Gay
AISTATS 2019 Sample Complexity of Sinkhorn Divergences Aude Genevay, Lénaïc Chizat, Francis Bach, Marco Cuturi, Gabriel Peyré
AISTATS 2019 Sharp Analysis of Learning with Discrete Losses Alex Nowak, Francis Bach, Alessandro Rudi
AISTATS 2019 Stochastic Algorithms with Descent Guarantees for ICA Pierre Ablin, Alexandre Gramfort, Jean-François Cardoso, Francis Bach
COLT 2019 Stochastic First-Order Methods: Non-Asymptotic and Computer-Aided Analyses via Potential Functions Adrien Taylor, Francis Bach
NeurIPS 2019 Towards Closing the Gap Between the Theory and Practice of SVRG Othmane Sebbouh, Nidham Gazagnadou, Samy Jelassi, Francis Bach, Robert Gower
NeurIPS 2019 UniXGrad: A Universal, Adaptive Algorithm with Optimal Guarantees for Constrained Optimization Ali Kavis, Kfir Y. Levy, Francis Bach, Volkan Cevher
NeurIPS 2018 Efficient Algorithms for Non-Convex Isotonic Regression Through Submodular Optimization Francis Bach
NeurIPS 2018 On the Global Convergence of Gradient Descent for Over-Parameterized Models Using Optimal Transport Lénaïc Chizat, Francis Bach
NeurIPS 2018 Optimal Algorithms for Non-Smooth Distributed Optimization in Networks Kevin Scaman, Francis Bach, Sebastien Bubeck, Laurent Massoulié, Yin Tat Lee
NeurIPS 2018 REST-Katyusha: Exploiting the Solution's Structure via Scheduled Restart Schemes Junqi Tang, Mohammad Golbabaee, Francis Bach, Mike E Davies
NeurIPS 2018 Relating Leverage Scores and Density Using Regularized Christoffel Functions Edouard Pauwels, Francis Bach, Jean-Philippe Vert
NeurIPS 2018 SING: Symbol-to-Instrument Neural Generator Alexandre Defossez, Neil Zeghidour, Nicolas Usunier, Leon Bottou, Francis Bach
NeurIPS 2018 Statistical Optimality of Stochastic Gradient Descent on Hard Learning Problems Through Multiple Passes Loucas Pillaud-Vivien, Alessandro Rudi, Francis Bach
JMLR 2017 Active-Set Methods for Submodular Minimization Problems K. S. Sesh Kumar, Francis Bach
JMLR 2017 Breaking the Curse of Dimensionality with Convex Neural Networks Francis Bach
JMLR 2017 Harder, Better, Faster, Stronger Convergence Rates for Least-Squares Regression Aymeric Dieuleveut, Nicolas Flammarion, Francis Bach
NeurIPS 2017 Integration Methods and Optimization Algorithms Damien Scieur, Vincent Roulet, Francis Bach, Alexandre d'Aspremont
CVPR 2017 Kernel Square-Loss Exemplar Machines for Image Retrieval Rafael S. Rezende, Joaquin Zepeda, Jean Ponce, Francis Bach, Patrick Perez
NeurIPS 2017 Nonlinear Acceleration of Stochastic Algorithms Damien Scieur, Francis Bach, Alexandre d'Aspremont
NeurIPS 2017 On Structured Prediction Theory with Calibrated Convex Surrogate Losses Anton Osokin, Francis Bach, Simon Lacoste-Julien
JMLR 2017 On the Consistency of Ordinal Regression Methods Fabian Pedregosa, Francis Bach, Alexandre Gramfort
JMLR 2017 On the Equivalence Between Kernel Quadrature Rules and Random Feature Expansions Francis Bach
JMLR 2017 Online but Accurate Inference for Latent Variable Models with Local Gibbs Sampling Christophe Dupuy, Francis Bach
ICML 2017 Optimal Algorithms for Smooth and Strongly Convex Distributed Optimization in Networks Kevin Scaman, Francis Bach, Sébastien Bubeck, Yin Tat Lee, Laurent Massoulié
JMLR 2017 Robust Discriminative Clustering with Sparse Regularizers Nicolas Flammarion, Balamurugan Palaniappan, Francis Bach
COLT 2017 Stochastic Composite Least-Squares Regression with Convergence Rate $O(1/n)$ Nicolas Flammarion, Francis Bach
ICML 2016 Beyond CCA: Moment Matching for Multi-View Models Anastasia Podosinnikova, Francis Bach, Simon Lacoste-Julien
NeurIPS 2016 PAC-Bayesian Theory Meets Bayesian Inference Pascal Germain, Francis Bach, Alexandre Lacoste, Simon Lacoste-Julien
NeurIPS 2016 Parameter Learning for Log-Supermodular Distributions Tatiana Shpakova, Francis Bach
NeurIPS 2016 Regularized Nonlinear Acceleration Damien Scieur, Alexandre d'Aspremont, Francis Bach
NeurIPS 2016 Stochastic Optimization for Large-Scale Optimal Transport Aude Genevay, Marco Cuturi, Gabriel Peyré, Francis Bach
NeurIPS 2016 Stochastic Variance Reduction Methods for Saddle-Point Problems Balamurugan Palaniappan, Francis Bach
NeurIPS 2015 Rethinking LDA: Moment Matching for Discrete ICA Anastasia Podosinnikova, Francis Bach, Simon Lacoste-Julien
NeurIPS 2015 Spectral Norm Regularization of Orthonormal Representations for Graph Transduction Rakesh Shivanna, Bibaswan K Chatterjee, Raman Sankaran, Chiranjib Bhattacharyya, Francis Bach
ICCV 2015 Weakly-Supervised Alignment of Video with Text Piotr Bojanowski, Remi Lajugie, Edouard Grave, Francis Bach, Ivan Laptev, Jean Ponce, Cordelia Schmid
JMLR 2014 Adaptivity of Averaged Stochastic Gradient Descent to Local Strong Convexity for Logistic Regression Francis Bach
ICML 2014 Large-Margin Metric Learning for Constrained Partitioning Problems Rémi Lajugie, Francis Bach, Sylvain Arlot
NeurIPS 2014 Metric Learning for Temporal Sequence Alignment Damien Garreau, Rémi Lajugie, Sylvain Arlot, Francis Bach
NeurIPS 2014 SAGA: A Fast Incremental Gradient Method with Support for Non-Strongly Convex Composite Objectives Aaron Defazio, Francis Bach, Simon Lacoste-Julien
ICML 2013 Convex Relaxations for Learning Bounded-Treewidth Decomposable Graphs K. S. Sesh Kumar, Francis Bach
NeurIPS 2013 Convex Relaxations for Permutation Problems Fajwel Fogel, Rodolphe Jenatton, Francis Bach, Alexandre D'Aspremont
ICML 2013 Intersecting Singularities for Multi-Structured Estimation Emile Richard, Francis Bach, Jean-Philippe Vert
ICML 2013 Learning Sparse Penalties for Change-Point Detection Using Max Margin Interval Regression Toby Hocking, Guillem Rigaill, Jean-Philippe Vert, Francis Bach
NeurIPS 2013 Non-Strongly-Convex Smooth Stochastic Approximation with Convergence Rate O(1/n) Francis Bach, Eric Moulines
NeurIPS 2013 Reflection Methods for User-Friendly Submodular Optimization Stefanie Jegelka, Francis Bach, Suvrit Sra
JMLR 2012 Multi-Task Regression Using Minimal Penalties Matthieu Solnon, Sylvain Arlot, Francis Bach
JMLR 2011 Convex and Network Flow Optimization for Structured Sparsity Julien Mairal, Rodolphe Jenatton, Guillaume Obozinski, Francis Bach
JMLR 2011 Proximal Methods for Hierarchical Sparse Coding Rodolphe Jenatton, Julien Mairal, Guillaume Obozinski, Francis Bach
JMLR 2011 Structured Variable Selection with Sparsity-Inducing Norms Rodolphe Jenatton, Jean-Yves Audibert, Francis Bach
JMLR 2010 Online Learning for Matrix Factorization and Sparse Coding Julien Mairal, Francis Bach, Jean Ponce, Guillermo Sapiro
AISTATS 2010 Structured Sparse Principal Component Analysis Rodolphe Jenatton, Guillaume Obozinski, Francis Bach
JMLR 2009 A New Approach to Collaborative Filtering: Operator Estimation with Spectral Regularization Jacob Abernethy, Francis Bach, Theodoros Evgeniou, Jean-Philippe Vert
JMLR 2008 Optimal Solutions for Sparse Principal Component Analysis Alexandre d'Aspremont, Francis Bach, Laurent El Ghaoui
AISTATS 2005 On the Path to an Ideal ROC Curve: Considering Cost Asymmetry in Learning Classifiers Francis Bach, David Heckerman, Eric Horvitz