Francis Bach
- Learning with Differentiable Perturbed Optimizers
2020/02/20 by Quentin Berthet, Mathieu Blondel, Berthet, Quentin +9 · 4 voices · 6 citations
#cs.LG #math.OC #stat.ML
- SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly\n Convex Composite Objectives
2014/07/01 by Aaron Defazio, Defazio, Aaron, Francis Bach +3 · 59 citations
Computer Science · Engineering · Mathematics · #Advanced Optimization Algorithms Research #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC) #Optimization and Variational Analysis #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
- Breaking the Curse of Dimensionality with Convex Neural Networks
2014/12/30 by Francis Bach, Bach, Francis · 30 citations
Computer Science · #Stochastic Gradient Optimization Techniques #Machine Learning and Algorithms #Machine Learning and ELM
- Non-strongly-convex smooth stochastic approximation with convergence rate O(1/n)
2013/06/10 by Francis Bach, Éric Moulines, Bach, Francis +1 · 34 citations
Computer Science · Engineering · #Stochastic Gradient Optimization Techniques #Sparse and Compressive Sensing Techniques #Machine Learning and Algorithms
- Stochastic Optimization for Large-scale Optimal Transport
2016/05/27 by Aude Genevay, Marco Cuturi, Aude, Genevay +5 · 28 citations
Mathematics · Computer Science · #Markov Chains and Monte Carlo Methods #Stochastic Gradient Optimization Techniques #Gaussian Processes and Bayesian Inference
- Sample Complexity of Sinkhorn divergences
2018/10/05 by Aude Genevay, Genevay, Aude, Lénaïc Chizat +7 · 29 citations
Computer Science · Decision Sciences · #Adversarial Robustness in Machine Learning #FOS: Mathematics #Machine Learning and Algorithms #Probabilistic and Robust Engineering Design #Statistics Theory (math.ST)
- Bridging the Gap between Constant Step Size Stochastic Gradient Descent and Markov Chains
2017/07/20 by Aymeric Dieuleveut, Alain Durmus, Dieuleveut, Aymeric +3 · 15 citations
Computer Science · Mathematics · Physics and Astronomy · #Stochastic Gradient Optimization Techniques #Markov Chains and Monte Carlo Methods #stochastic dynamics and bifurcation
- Consistency of the group Lasso and multiple kernel learning
2007/07/23 by Francis Bach, Bach, Francis · 13 citations
Computer Science · Mathematics · Medicine · #Bayesian Methods and Mixture Models #FOS: Computer and information sciences #Machine Learning (cs.LG) #Statistical Methods and Inference #Systemic Lupus Erythematosus Research
- On the Equivalence between Kernel Quadrature Rules and Random Feature Expansions
2015/02/24 by Francis Bach, Bach, Francis · 12 citations
Computer Science · Mathematics · #FOS: Computer and information sciences #FOS: Mathematics #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Mathematical Approximation and Integration #Numerical Analysis (math.NA) #Stochastic Gradient Optimization Techniques
- Optimal algorithms for smooth and strongly convex distributed optimization in networks
2017/02/28 by Francis Bach, Scaman, Kevin, Sébastien Bubeck +6 · 12 citations
Computer Science · Engineering · #Distributed Control Multi-Agent Systems #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (stat.ML) #Optimization and Control (math.OC) #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
- Bridging the gap between constant step size stochastic gradient descent and Markov chains
2020/06/01 by Aymeric Dieuleveut, Alain Durmus, Francis Bach · 12 citations
- Music Source Separation in the Waveform Domain
2019/11/27 by Alexandre Défossez, Nicolas Usunier, Défossez, Alexandre +5 · 15 citations
Computer Science · #Speech and Audio Processing #Music and Audio Processing #Speech Recognition and Synthesis
- A Simple Convergence Proof of Adam and Adagrad
2020/03/05 by Alexandre Défossez, Léon Bottou, Défossez, Alexandre +5 · 11 citations
Computer Science · Decision Sciences · Engineering · #Advanced Bandit Algorithms Research #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
- Consistency of trace norm minimization
2007/10/15 by Francis Bach, Bach, Francis · 12 citations
Mathematics · Engineering · Computer Science · #Statistical Methods and Inference #Fault Detection and Control Systems #Machine Learning and Algorithms
- Implicit Regularization of Discrete Gradient Dynamics in Linear Neural\n Networks
2019/04/30 by Gauthier Gidel, Gidel, Gauthier, Francis Bach +3 · 9 citations
Computer Science · Engineering · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and ELM #Optimization and Control (math.OC) #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
- Variational inference via Wasserstein gradient flows
2022/05/31 by Marc Lambert, Lambert, Marc, Sinho Chewi +7 · 11 citations
Computer Science · Mathematics · #FOS: Computer and information sciences #FOS: Mathematics #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Markov Chains and Monte Carlo Methods #Statistical Methods and Inference #Statistics Theory (math.ST)
- Structured Sparse Principal Component Analysis
2009/09/08 by Rodolphe Jenatton, Jenatton, Rodolphe, Guillaume Obozinski +3 · 7 citations
Computer Science · Engineering · #Blind Source Separation Techniques #FOS: Computer and information sciences #Face and Expression Recognition #Machine Learning (stat.ML) #Sparse and Compressive Sensing Techniques
- Harder, Better, Faster, Stronger Convergence Rates for Least-Squares Regression
2016/02/17 by Dieuleveut, Aymeric, Nicolas Flammarion, Francis Bach +3 · 7 citations
Computer Science · Decision Sciences · Engineering · #Advanced Bandit Algorithms Research #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Optimization and Control (math.OC) #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
- Exploring Large Feature Spaces with Hierarchical Multiple Kernel Learning
2008/09/09 by Francis Bach, Bach, Francis · 6 citations
Computer Science · #Domain Adaptation and Few-Shot Learning #Machine Learning and ELM #Face and Expression Recognition
- A path following algorithm for the graph matching problem
2008/01/23 by Mikhail Zaslavskiy, Francis Bach, Zaslavskiy, Mikhail +3 · 4 citations
Computer Science · Decision Sciences · #Advanced Image and Video Retrieval Techniques #Computer Vision and Pattern Recognition (cs.CV) #Data Quality and Management #Discrete Mathematics (cs.DM) #FOS: Computer and information sciences #Graph Theory and Algorithms
- The Surprising Agreement Between Convex Optimization Theory and Learning-Rate Scheduling for Large Model Training
2025/01/31 by Fabian Schaipp, Schaipp, Fabian, Alexander Hägele +7 · 2 voices · 12 citations
#cs.LG #math.OC #stat.ML
- Optimal Solutions for Sparse Principal Component Analysis
2007/07/04 by Alexandre d’Aspremont, Francis Bach, d'Aspremont, Alexandre +3 · 3 citations
Engineering · Computer Science · #Sparse and Compressive Sensing Techniques #Blind Source Separation Techniques #Face and Expression Recognition
- Bolasso: model consistent Lasso estimation through the bootstrap
2008/04/08 by Francis Bach, Bach, Francis · 3 citations
Economics, Econometrics and Finance · Mathematics · #FOS: Computer and information sciences #FOS: Mathematics #Financial Risk and Volatility Modeling #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistical Methods and Inference #Statistics Theory (math.ST) #Stochastic processes and financial applications
- A Universal Algorithm for Variational Inequalities Adaptive to Smoothness and Noise
2019/02/05 by Francis Bach, Kfir Y. Levy, Bach, Francis +1 · 4 citations
Engineering · Computer Science · Mathematics · #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques #Numerical methods in inverse problems
- On the Impact of Overparameterization on the Training of a Shallow Neural Network in High Dimensions
2023/11/07 by Martín Simón, Martin, Simon, Francis Bach +3 · 5 citations
Computer Science · Physics and Astronomy · #Neural Networks and Applications #Model Reduction and Neural Networks #Stochastic Gradient Optimization Techniques
- Deep Equals Shallow for ReLU Networks in Kernel Regimes
2020/09/30 by Alberto Bietti, Bietti, Alberto, Francis Bach +1 · 3 citations
Computer Science · Physics and Astronomy · #Advanced Graph Neural Networks #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks #Stochastic Gradient Optimization Techniques
- Non-parametric Models for Non-negative Functions
2020/07/08 by Ulysse Marteau-Ferey, Francis Bach, Marteau-Ferey, Ulysse +3 · 3 citations
Engineering · Mathematics · #Sparse and Compressive Sensing Techniques #Advanced Optimization Algorithms Research #Control Systems and Identification
- Sequential Kernel Herding: Frank-Wolfe Optimization for Particle Filtering
2015/01/09 by Simon Lacoste-Julien, Fredrik Lindsten, Lacoste-Julien, Simon +3 · 2 citations
Computer Science · Engineering · #Advanced Neural Network Applications #FOS: Computer and information sciences #Indoor and Outdoor Localization Technologies #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Stochastic Gradient Optimization Techniques
- Tight Nonparametric Convergence Rates for Stochastic Gradient Descent under the Noiseless Linear Model
2020/06/15 by Raphaël Berthier, Francis Bach, Berthier, Raphaël +3 · 3 citations
Mathematics · Engineering · Computer Science · #Statistical Methods and Inference #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
- Finite-sample analysis of M-estimators using self-concordance
2018/10/14 by Dmitrii M. Ostrovskii, Francis Bach, Ostrovskii, Dmitrii +1 · 2 citations
Mathematics · #Advanced Statistical Methods and Models #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (stat.ML) #Optimization and Control (math.OC) #Random Matrices and Applications #Statistical Methods and Bayesian Inference #Statistical Methods and Inference #Statistics Theory (math.ST)
- Accelerated Decentralized Optimization with Local Updates for Smooth and\n Strongly Convex Objectives
2018/10/05 by Hadrien Hendrikx, Francis Bach, Hendrikx, Hadrien +3 · 2 citations
Computer Science · Materials Science · #Cooperative Communication and Network Coding #Distributed #Distributed Control Multi-Agent Systems #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Nanocluster Synthesis and Applications #Neural Networks Stability and Synchronization #Optimization and Control (math.OC) #Parallel #and Cluster Computing (cs.DC)
- Relating Leverage Scores and Density using Regularized Christoffel Functions
2018/05/21 by Edouard Pauwels, Pauwels, Edouard, Francis R. Bach +4 · 2 citations
Computer Science · Engineering · Mathematics · #Bayesian Methods and Mixture Models #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Sparse and Compressive Sensing Techniques #Statistical Methods and Inference #Stochastic Gradient Optimization Techniques
- E-Values Expand the Scope of Conformal Prediction
2025/03/17 by Francis Bach, Gauthier, Etienne, Michael I. Jordan +2 · 9 citations
Computer Science · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural Networks and Applications
- Convergence Rates for Non-Log-Concave Sampling and Log-Partition Estimation
2023/03/06 by David Holzmüller, Francis Bach, Holzmüller, David +1 · 3 citations
Computer Science · Mathematics · #Bayesian Methods and Mixture Models #Computation (stat.CO) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Markov Chains and Monte Carlo Methods #Statistics Theory (math.ST)
- Rethinking Early Stopping: Refine, Then Calibrate
2025/01/31 by Eugène Berta, Berta, Eugène, David Holzmüller +5 · 4 voices · 3 citations
#cs.LG #cs.AI
- An Accelerated Decentralized Stochastic Proximal Algorithm for Finite Sums
2019/05/27 by Hadrien Hendrikx, Hendrikx, Hadrien, Francis Bach +3 · 3 citations
Computer Science · Engineering · #Stochastic Gradient Optimization Techniques #Sparse and Compressive Sensing Techniques #Privacy-Preserving Technologies in Data
- High-Dimensional Non-Linear Variable Selection through Hierarchical Kernel Learning
2009/09/04 by Francis Bach, Bach, Francis · 1 voice
#cs.LG #math.ST
- On Structured Prediction Theory with Calibrated Convex Surrogate Losses
2017/03/07 by Anton Osokin, Osokin, Anton, Francis Bach +3 · 1 citation
Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #Adversarial Robustness in Machine Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Stochastic Gradient Optimization Techniques
- Constant Step Size Stochastic Gradient Descent for Probabilistic Modeling
2018/04/16 by Dmitry T. Babichev, Babichev, Dmitry, Francis Bach +1 · 2 citations
Computer Science · #Stochastic Gradient Optimization Techniques #Machine Learning and Algorithms #Domain Adaptation and Few-Shot Learning
- Physics-informed kernel learning
2024/09/20 by Nathan Doumèche, Francis Bach, Doumèche, Nathan +5 · 3 citations
Computer Science · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural Networks and Applications #Statistics Theory (math.ST)
- Accelerated Gossip in Networks of Given Dimension using Jacobi Polynomial Iterations
2018/05/22 by Raphaël Berthier, Francis Bach, Berthier, Raphaël +3 · 1 citation
Computer Science · Physics and Astronomy · #Distributed #Distributed Control Multi-Agent Systems #FOS: Computer and information sciences #Machine Learning (stat.ML) #Multiagent Systems (cs.MA) #Neural Networks Stability and Synchronization #Opinion Dynamics and Social Influence #Parallel #and Cluster Computing (cs.DC)
- Beyond Least-Squares: Fast Rates for Regularized Empirical Risk Minimization through Self-Concordance
2019/02/08 by Ulysse Marteau-Ferey, Marteau-Ferey, Ulysse, Dmitrii M. Ostrovskii +5 · 3 citations
Computer Science · Engineering · Mathematics · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #FOS: Mathematics #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning and Algorithms #Sparse and Compressive Sensing Techniques #Statistical Methods and Inference #Statistics Theory (math.ST) #Stochastic Gradient Optimization Techniques
- Weakly Supervised Action Labeling in Videos Under Ordering Constraints
2014/07/04 by Piotr Bojanowski, Bojanowski, Piotr, Rémi Lajugie +11 · 1 citation
Computer Science · Engineering · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Human Motion and Animation #Human Pose and Action Recognition #Machine Learning (cs.LG) #Video Analysis and Summarization
- Optimal Denoising in Score-Based Generative Models: The Role of Data Regularity
2025/03/17 by Eliot Beyler, Beyler, Eliot, Francis Bach +1 · 3 citations
Mathematics · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistical Methods and Inference
- Universal Smoothed Score Functions for Generative Modeling
2023/03/21 by Saeed Saremi, Saremi, Saeed, Rupesh K. Srivastava +3 · 1 citation
Computer Science · #Bayesian Methods and Mixture Models #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning in Healthcare #Topic Modeling
- Nonparametric Linear Feature Learning in Regression Through Regularisation
2023/07/24 by Bertille Follain, Follain, Bertille, Francis Bach +1 · 1 citation
Chemistry · Computer Science · Mathematics · #62F10 (Primary) #62G08 #65K10 (Secondary) #Advanced Statistical Methods and Models #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #FOS: Mathematics #I.2.6 #Machine Learning (cs.LG) #Methodology (stat.ME) #Neural Networks and Applications #Spectroscopy and Chemometric Analyses #Statistics Theory (math.ST)
- Multiple Operator-valued Kernel Learning
2012/01/01 by Hachem Kadri, Kadri, Hachem, Alain Rakotomamonjy +4 · 2 citations
Computer Science · Materials Science · Neuroscience · #Blind Source Separation Techniques #EEG and Brain-Computer Interfaces #FOS: Computer and information sciences #Functional Brain Connectivity Studies #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning in Materials Science #Neural Networks and Applications #Neural dynamics and brain function
- Online Regularized Nonlinear Acceleration
2018/05/24 by Damien Scieur, Edouard Oyallon, Scieur, Damien +5 · 1 citation
Computer Science · Engineering · Mathematics · #Advanced Optimization Algorithms Research #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC) #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
- Convergence of Deterministic and Stochastic Diffusion-Model Samplers: A Simple Analysis in Wasserstein Distance
2025/08/05 by Eliot Beyler, Francis Bach, Beyler, Eliot +1 · 3 citations
Economics, Econometrics and Finance · Mathematics · Decision Sciences · #Stochastic processes and financial applications #Markov Chains and Monte Carlo Methods #Probabilistic and Robust Engineering Design
- Batch Normalization Provably Avoids Rank Collapse for Randomly Initialised Deep Networks
2020/03/03 by Hadi Daneshmand, Jonas Köhler, Daneshmand, Hadi +7 · 1 citation
Computer Science · Engineering · #FOS: Computer and information sciences #Face and Expression Recognition #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques