Francis R. Bach

ORCID

Publication Activity (10 Years)

Years Active: 2001-2024
Publications (10 Years): 245

Top Venues

Publications

Adrien Vacher, Boris Muzellec, Francis R. Bach, François-Xavier Vialard, Alessandro Rudi
Optimal Estimation of Smooth Transport Maps with Kernel SoS. SIAM J. Math. Data Sci. 6 (2) (2024)
Silvère Bonnabel, Marc Lambert, Francis R. Bach
Low-rank plus diagonal approximations for Riccati-like matrix differential equations. CoRR (2024)
Saeed Saremi, Ji Won Park, Francis R. Bach
Chain of Log-Concave Markov Chains. ICLR (2024)
Eugene Berta, Francis R. Bach, Michael I. Jordan
Classifier Calibration with ROC-Regularized Isotonic Regression. AISTATS (2024)
Ulysse Marteau-Ferey, Francis R. Bach, Alessandro Rudi
Second Order Conditions to Decompose Smooth Functions as Sums of Squares. SIAM J. Optim. 34 (1) (2024)
Antonio Orvieto, Anant Raj, Hans Kersting, Francis R. Bach
Explicit Regularization in Overparametrized Models via Noise Injection. AISTATS (2023)
Francis R. Bach, Alessandro Rudi
Exponential Convergence of Sum-of-Squares Hierarchies for Trigonometric Polynomials. SIAM J. Optim. 33 (3) (2023)
Loucas Pillaud-Vivien, Francis R. Bach
Kernelized Diffusion Maps. COLT (2023)
Lawrence Stewart, Francis R. Bach, Quentin Berthet, Jean-Philippe Vert
Regression as Classification: Influence of Task Formulation on Neural Network Features. AISTATS (2023)
Francis R. Bach, Elisabetta Cornacchia, Luca Pesce, Giovanni Piccioli
Theory and applications of the Sum-Of-Squares technique. CoRR (2023)
Céline Moucer, Adrien B. Taylor, Francis R. Bach
A Systematic Approach to Lyapunov Analyses of Continuous-Time Models in Convex Optimization. SIAM J. Optim. 33 (3) (2023)
Belinda Tzen, Anant Raj, Maxim Raginsky, Francis R. Bach
Variational Principles for Mirror Descent and Mirror Langevin Dynamics. IEEE Control. Syst. Lett. 7 (2023)
Amir Joudaki, Hadi Daneshmand, Francis R. Bach
On the impact of activation and normalization in obtaining isometric embeddings at initialization. CoRR (2023)
Loucas Pillaud-Vivien, Francis R. Bach
Kernelized Diffusion maps. CoRR (2023)
Blake E. Woodworth, Konstantin Mishchenko, Francis R. Bach
Two Losses Are Better Than One: Faster Optimization Using a Cheaper Proxy. CoRR (2023)
Marc Lambert, Silvère Bonnabel, Francis R. Bach
Variational Gaussian approximation of the Kushner optimal filter. CoRR (2023)
Blake E. Woodworth, Konstantin Mishchenko, Francis R. Bach
Two Losses Are Better Than One: Faster Optimization Using a Cheaper Proxy. ICML (2023)
Marc Lambert, Silvère Bonnabel, Francis R. Bach
The limited-memory recursive variational Gaussian approximation (L-RVGA). CoRR (2023)
Saeed Saremi, Ji Won Park, Francis R. Bach
Chain of Log-Concave Markov Chains. CoRR (2023)
Mathieu Barré, Adrien B. Taylor, Francis R. Bach
Principled analyses and design of first-order methods with inexact proximal operators. Math. Program. 201 (1) (2023)
Lawrence Stewart, Francis R. Bach, Felipe Llinares-López, Quentin Berthet
Differentiable Clustering with Perturbed Spanning Forests. NeurIPS (2023)
Marc Lambert, Silvère Bonnabel, Francis R. Bach
Variational Gaussian Approximation of the Kushner Optimal Filter. GSI (1) (2023)
Marc Lambert, Silvère Bonnabel, Francis R. Bach
The limited-memory recursive variational Gaussian approximation (L-RVGA). Stat. Comput. 33 (3) (2023)
Lawrence Stewart, Francis R. Bach, Felipe Llinares-López, Quentin Berthet
Differentiable Clustering with Perturbed Spanning Forests. CoRR (2023)
Amir Joudaki, Hadi Daneshmand, Francis R. Bach
On the impact of activation and normalization in obtaining isometric embeddings at initialization. NeurIPS (2023)
Amir Joudaki, Hadi Daneshmand, Francis R. Bach
On Bridging the Gap between Mean Field and Finite Width Deep Random Multilayer Perceptron with Batch Normalization. ICML (2023)
Eugene Berta, Francis R. Bach, Michael I. Jordan
Classifier Calibration with ROC-Regularized Isotonic Regression. CoRR (2023)
Belinda Tzen, Anant Raj, Maxim Raginsky, Francis R. Bach
Variational Principles for Mirror Descent and Mirror Langevin Dynamics. CoRR (2023)
Blake E. Woodworth, Francis R. Bach, Alessandro Rudi
Non-Convex Optimization with Certificates and Fast Rates Through Kernel Sums of Squares. CoRR (2022)
Marc Lambert, Silvère Bonnabel, Francis R. Bach
The continuous-discrete variational Kalman filter (CD-VKF). CDC (2022)
Anant Raj, Francis R. Bach
Convergence of Uncertainty Sampling for Active Learning. ICML (2022)
Antonio Orvieto, Hans Kersting, Frank Proske, Francis R. Bach, Aurélien Lucchi
Anticorrelated Noise Injection for Improved Generalization. ICML (2022)
Aurélien Lucchi, Frank Proske, Antonio Orvieto, Francis R. Bach, Hans Kersting
On the Theoretical Properties of Noise Correlation in Stochastic Optimization. CoRR (2022)
Lawrence Stewart, Francis R. Bach, Quentin Berthet, Jean-Philippe Vert
Regression as Classification: Influence of Task Formulation on Neural Network Features. CoRR (2022)
Blake E. Woodworth, Francis R. Bach, Alessandro Rudi
Non-Convex Optimization with Certificates and Fast Rates Through Kernel Sums of Squares. COLT (2022)
Antonio Orvieto, Anant Raj, Hans Kersting, Francis R. Bach
Explicit Regularization in Overparametrized Models via Noise Injection. CoRR (2022)
Vivien Cabannes, Francis R. Bach, Vianney Perchet, Alessandro Rudi
Active Labeling: Streaming Stochastic Gradients. CoRR (2022)
Konstantin Mishchenko, Francis R. Bach, Mathieu Even, Blake E. Woodworth
Asynchronous SGD Beats Minibatch SGD Under Arbitrary Delays. CoRR (2022)
Théo Ryffel, Francis R. Bach, David Pointcheval
Differential Privacy Guarantees for Stochastic Gradient Langevin Dynamics. CoRR (2022)
Céline Moucer, Adrien B. Taylor, Francis R. Bach
A systematic approach to Lyapunov analyses of continuous-time models in convex optimization. CoRR (2022)
Hadi Daneshmand, Francis R. Bach
Polynomial-time sparse measure recovery. CoRR (2022)
Alexandre Défossez, Léon Bottou, Francis R. Bach, Nicolas Usunier
A Simple Convergence Proof of Adam and Adagrad. Trans. Mach. Learn. Res. 2022 (2022)
Benjamin Dubois-Taine, Francis R. Bach, Quentin Berthet, Adrien B. Taylor
Fast Stochastic Composite Minimization and an Accelerated Frank-Wolfe Algorithm under Parallelization. NeurIPS (2022)
Yifan Sun, Francis R. Bach
Screening for a Reweighted Penalized Conditional Gradient Method. Open J. Math. Optim. 3 (2022)
Mathieu Barré, Adrien B. Taylor, Francis R. Bach
A note on approximate accelerated forward-backward methods with absolute and relative errors, and possibly strongly convex objectives. Open J. Math. Optim. 3 (2022)
Marc Lambert, Sinho Chewi, Francis R. Bach, Silvère Bonnabel, Philippe Rigollet
Variational inference via Wasserstein gradient flows. NeurIPS (2022)
Ulysse Marteau-Ferey, Francis R. Bach, Alessandro Rudi
Sampling from Arbitrary Functions via PSD Models. AISTATS (2022)
Marc Lambert, Sinho Chewi, Francis R. Bach, Silvère Bonnabel, Philippe Rigollet
Variational inference via Wasserstein gradient flows. CoRR (2022)
Konstantin Mishchenko, Francis R. Bach, Mathieu Even, Blake E. Woodworth
Asynchronous SGD Beats Minibatch SGD Under Arbitrary Delays. NeurIPS (2022)
Benjamin Dubois-Taine, Francis R. Bach, Quentin Berthet, Adrien B. Taylor
Fast Stochastic Composite Minimization and an Accelerated Frank-Wolfe Algorithm under Parallelization. CoRR (2022)
Antonio Orvieto, Hans Kersting, Frank Proske, Francis R. Bach, Aurélien Lucchi
Anticorrelated Noise Injection for Improved Generalization. CoRR (2022)
Amir Joudaki, Hadi Daneshmand, Francis R. Bach
Entropy Maximization with Depth: A Variational Principle for Random Neural Networks. CoRR (2022)
Théo Ryffel, Pierre Tholoniat, David Pointcheval, Francis R. Bach
AriaNN: Low-Interaction Privacy-Preserving Deep Learning via Function Secret Sharing. Proc. Priv. Enhancing Technol. 2022 (1) (2022)
Vivien Cabannes, Francis R. Bach, Vianney Perchet, Alessandro Rudi
Active Labeling: Streaming Stochastic Gradients. NeurIPS (2022)
Eloïse Berthier, Justin Carpentier, Alessandro Rudi, Francis R. Bach
Infinite-Dimensional Sums-of-Squares for Optimal Control. CDC (2022)
Eloïse Berthier, Ziad Kobeissi, Francis R. Bach
A Non-asymptotic Analysis of Non-parametric Temporal-Difference Learning. NeurIPS (2022)
Alex Nowak, Alessandro Rudi, Francis R. Bach
On the Consistency of Max-Margin Losses. AISTATS (2022)
Aurélien Lucchi, Frank Proske, Antonio Orvieto, Francis R. Bach, Hans Kersting
On the Theoretical Properties of Noise Correlation in Stochastic Optimization. NeurIPS (2022)
Vivien Cabannes, Alessandro Rudi, Francis R. Bach
Fast rates in structured prediction. CoRR (2021)
Hadi Daneshmand, Amir Joudaki, Francis R. Bach
Batch Normalization Orthogonalizes Representations in Deep Random Networks. NeurIPS (2021)
Vivien Cabannes, Loucas Pillaud-Vivien, Francis R. Bach, Alessandro Rudi
Overcoming the curse of dimensionality with Laplacian regularization in semi-supervised learning. NeurIPS (2021)
Vivien Cabannes, Francis R. Bach, Alessandro Rudi
Disambiguation of weak supervision with exponential convergence rates. CoRR (2021)
Vivien A. Cabannes, Francis R. Bach, Alessandro Rudi
Disambiguation of Weak Supervision leading to Exponential Convergence rates. ICML (2021)
Ulysse Marteau-Ferey, Francis R. Bach, Alessandro Rudi
Sampling from Arbitrary Functions via PSD Models. CoRR (2021)
Hadi Daneshmand, Amir Joudaki, Francis R. Bach
Batch Normalization Orthogonalizes Representations in Deep Random Networks. CoRR (2021)
Boris Muzellec, Adrien Vacher, Francis R. Bach, François-Xavier Vialard, Alessandro Rudi
Near-optimal estimation of smooth transport maps with kernel sums-of-squares. CoRR (2021)
Vivien A. Cabannes, Francis R. Bach, Alessandro Rudi
Fast Rates for Structured Prediction. COLT (2021)
Boris Muzellec, Francis R. Bach, Alessandro Rudi
A Note on Optimizing Distributions using Kernel Mean Embeddings. CoRR (2021)
Hadrien Hendrikx, Francis R. Bach, Laurent Massoulié
An Optimal Algorithm for Decentralized Finite-Sum Optimization. SIAM J. Optim. 31 (4) (2021)
Anant Raj, Francis R. Bach
Explicit Regularization of Stochastic Gradient Methods through Duality. AISTATS (2021)
Yifan Sun, Francis R. Bach
Screening for a Reweighted Penalized Conditional Gradient Method. CoRR (2021)
Mathieu Even, Raphaël Berthier, Francis R. Bach, Nicolas Flammarion, Hadrien Hendrikx, Pierre Gaillard, Laurent Massoulié, Adrien B. Taylor
Continuized Accelerations of Deterministic and Stochastic Gradient Descents, and of Gossip Algorithms. NeurIPS (2021)
Francis R. Bach, Lenaïc Chizat
Gradient Descent on Infinitely Wide Neural Networks: Global Convergence and Generalization. CoRR (2021)
Mathieu Even, Raphaël Berthier, Francis R. Bach, Nicolas Flammarion, Pierre Gaillard, Hadrien Hendrikx, Laurent Massoulié, Adrien Taylor
A Continuized View on Nesterov Acceleration for Stochastic Gradient Descent and Randomized Gossip. CoRR (2021)
Francis R. Bach
On the Effectiveness of Richardson Extrapolation in Data Science. SIAM J. Math. Data Sci. 3 (4) (2021)
Boris Muzellec, Francis R. Bach, Alessandro Rudi
Learning PSD-valued functions using kernel sums-of-squares. CoRR (2021)
Adrien Vacher, Boris Muzellec, Alessandro Rudi, Francis R. Bach, François-Xavier Vialard
A Dimension-free Computational Upper-bound for Smooth Optimal Transport Estimation. COLT (2021)
Alex Nowak-Vila, Alessandro Rudi, Francis R. Bach
Max-Margin is Dead, Long Live Max-Margin! CoRR (2021)
Robert M. Gower, Peter Richtárik, Francis R. Bach
Stochastic quasi-gradient methods: variance reduction via Jacobian sketching. Math. Program. 188 (1) (2021)
Anant Raj, Francis R. Bach
Convergence of Uncertainty Sampling for Active Learning. CoRR (2021)
Alberto Bietti, Francis R. Bach
Deep Equals Shallow for ReLU Networks in Kernel Regimes. ICLR (2021)
Eloïse Berthier, Justin Carpentier, Francis R. Bach
Fast and Robust Stability Region Estimation for Nonlinear Dynamical Systems. ECC (2021)
Raphaël Berthier, Francis R. Bach, Nicolas Flammarion, Pierre Gaillard, Adrien Taylor
A Continuized View on Nesterov Acceleration. CoRR (2021)
Alexandre Défossez, Léon Bottou, Francis R. Bach, Nicolas Usunier
On the Convergence of Adam and Adagrad. CoRR (2020)
Damien Scieur, Alexandre d'Aspremont, Francis R. Bach
Regularized nonlinear acceleration. Math. Program. 179 (1) (2020)
Marin Ballu, Quentin Berthet, Francis R. Bach
Stochastic Optimization for Regularized Wasserstein Estimators. ICML (2020)
Raman Sankaran, Francis R. Bach, Chiranjib Bhattacharyya
Learning With Subquadratic Regularization : A Primal-Dual Approach. IJCAI (2020)
Hadrien Hendrikx, Francis R. Bach, Laurent Massoulié
Dual-Free Stochastic Decentralized Optimization with Variance Reduction. CoRR (2020)
Ulysse Marteau-Ferey, Francis R. Bach, Alessandro Rudi
Non-parametric Models for Non-negative Functions. CoRR (2020)
Raphaël Berthier, Francis R. Bach, Pierre Gaillard
Accelerated Gossip in Networks of Given Dimension Using Jacobi Polynomial Iterations. SIAM J. Math. Data Sci. 2 (1) (2020)
Marin Ballu, Quentin Berthet, Francis R. Bach
Stochastic Optimization for Regularized Wasserstein Estimators. CoRR (2020)
Hadrien Hendrikx, Lin Xiao, Sébastien Bubeck, Francis R. Bach, Laurent Massoulié
Statistically Preconditioned Accelerated Gradient Method for Distributed Optimization. ICML (2020)
Hadrien Hendrikx, Lin Xiao, Sébastien Bubeck, Francis R. Bach, Laurent Massoulié
Statistically Preconditioned Accelerated Gradient Method for Distributed Optimization. CoRR (2020)
Hadi Daneshmand, Jonas Moritz Kohler, Francis R. Bach, Thomas Hofmann, Aurélien Lucchi
Batch normalization provably avoids ranks collapse for randomly initialised deep networks. NeurIPS (2020)
Hadrien Hendrikx, Francis R. Bach, Laurent Massoulié
An Optimal Algorithm for Decentralized Finite Sum Optimization. CoRR (2020)
Alex Nowak, Francis R. Bach, Alessandro Rudi
Consistent Structured Prediction with Max-Min Margin Markov Networks. ICML (2020)
Raphaël Berthier, Francis R. Bach, Pierre Gaillard
Tight Nonparametric Convergence Rates for Stochastic Gradient Descent under the Noiseless Linear Model. CoRR (2020)
Raphaël Berthier, Francis R. Bach, Pierre Gaillard
Tight Nonparametric Convergence Rates for Stochastic Gradient Descent under the Noiseless Linear Model. NeurIPS (2020)
Vivien Cabannes, Alessandro Rudi, Francis R. Bach
Structured Prediction with Partial Labelling through the Infimum Loss. CoRR (2020)
Alessandro Rudi, Ulysse Marteau-Ferey, Francis R. Bach
Finding Global Minima via Kernel Approximations. CoRR (2020)

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Publication Activity (10 Years)

Top Topics

Top Venues

Francis R. Bach