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Structured Sparsity and convex optimization
Francis Bach
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Francis Bach (INRIA - Ecole Normale Superieure)
More from the Same Authors
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2021 Spotlight: Batch Normalization Orthogonalizes Representations in Deep Random Networks »
Hadi Daneshmand · Amir Joudaki · Francis Bach -
2022 Poster: A Non-asymptotic Analysis of Non-parametric Temporal-Difference Learning »
Eloïse Berthier · Ziad Kobeissi · Francis Bach -
2023 Poster: On the impact of activation and normalization in obtaining isometric embeddings at initialization »
Amir Joudaki · Hadi Daneshmand · Francis Bach -
2023 Poster: Differentiable Clustering with Perturbed Spanning Forests »
Lawrence Stewart · Francis Bach · Felipe Llinares-Lopez · Quentin Berthet -
2023 Poster: Regularization properties of adversarially-trained linear regression »
Antonio Ribeiro · Dave Zachariah · Francis Bach · Thomas Schön -
2022 Spotlight: Lightning Talks 1A-4 »
Siwei Wang · Jing Liu · Nianqiao Ju · Shiqian Li · Eloïse Berthier · Muhammad Faaiz Taufiq · Arsene Fansi Tchango · Chen Liang · Chulin Xie · Jordan Awan · Jean-Francois Ton · Ziad Kobeissi · Wenguan Wang · Xinwang Liu · Kewen Wu · Rishab Goel · Jiaxu Miao · Suyuan Liu · Julien Martel · Ruobin Gong · Francis Bach · Chi Zhang · Rob Cornish · Sanmi Koyejo · Zhi Wen · Yee Whye Teh · Yi Yang · Jiaqi Jin · Bo Li · Yixin Zhu · Vinayak Rao · Wenxuan Tu · Gaetan Marceau Caron · Arnaud Doucet · Xinzhong Zhu · Joumana Ghosn · En Zhu -
2022 Spotlight: A Non-asymptotic Analysis of Non-parametric Temporal-Difference Learning »
Eloïse Berthier · Ziad Kobeissi · Francis Bach -
2022 Poster: Variational inference via Wasserstein gradient flows »
Marc Lambert · Sinho Chewi · Francis Bach · Silvère Bonnabel · Philippe Rigollet -
2022 Poster: Asynchronous SGD Beats Minibatch SGD Under Arbitrary Delays »
Konstantin Mishchenko · Francis Bach · Mathieu Even · Blake Woodworth -
2022 Poster: On the Theoretical Properties of Noise Correlation in Stochastic Optimization »
Aurelien Lucchi · Frank Proske · Antonio Orvieto · Francis Bach · Hans Kersting -
2022 Poster: Fast Stochastic Composite Minimization and an Accelerated Frank-Wolfe Algorithm under Parallelization »
Benjamin Dubois-Taine · Francis Bach · Quentin Berthet · Adrien Taylor -
2022 Poster: Active Labeling: Streaming Stochastic Gradients »
Vivien Cabannes · Francis Bach · Vianney Perchet · Alessandro Rudi -
2021 Test Of Time: Online Learning for Latent Dirichlet Allocation »
Matthew Hoffman · Francis Bach · David Blei -
2021 Poster: Overcoming the curse of dimensionality with Laplacian regularization in semi-supervised learning »
Vivien Cabannes · Loucas Pillaud-Vivien · Francis Bach · Alessandro Rudi -
2021 Oral: Continuized Accelerations of Deterministic and Stochastic Gradient Descents, and of Gossip Algorithms »
Mathieu Even · Raphaël Berthier · Francis Bach · Nicolas Flammarion · Hadrien Hendrikx · Pierre Gaillard · Laurent Massoulié · Adrien Taylor -
2021 Poster: Batch Normalization Orthogonalizes Representations in Deep Random Networks »
Hadi Daneshmand · Amir Joudaki · Francis Bach -
2021 Poster: Continuized Accelerations of Deterministic and Stochastic Gradient Descents, and of Gossip Algorithms »
Mathieu Even · Raphaël Berthier · Francis Bach · Nicolas Flammarion · Hadrien Hendrikx · Pierre Gaillard · Laurent Massoulié · Adrien Taylor -
2020 : Francis Bach - Where is Machine Learning Going? »
Francis Bach -
2020 Poster: Tight Nonparametric Convergence Rates for Stochastic Gradient Descent under the Noiseless Linear Model »
Raphaël Berthier · Francis Bach · Pierre Gaillard -
2020 Poster: Learning with Differentiable Pertubed Optimizers »
Quentin Berthet · Mathieu Blondel · Olivier Teboul · Marco Cuturi · Jean-Philippe Vert · Francis Bach -
2020 Poster: Batch normalization provably avoids ranks collapse for randomly initialised deep networks »
Hadi Daneshmand · Jonas Kohler · Francis Bach · Thomas Hofmann · Aurelien Lucchi -
2020 Poster: Non-parametric Models for Non-negative Functions »
Ulysse Marteau-Ferey · Francis Bach · Alessandro Rudi -
2020 Spotlight: Non-parametric Models for Non-negative Functions »
Ulysse Marteau-Ferey · Francis Bach · Alessandro Rudi -
2020 Session: Orals & Spotlights Track 30: Optimization/Theory »
Yuxin Chen · Francis Bach -
2020 Poster: Dual-Free Stochastic Decentralized Optimization with Variance Reduction »
Hadrien Hendrikx · Francis Bach · Laurent Massoulié -
2019 Poster: Fast Decomposable Submodular Function Minimization using Constrained Total Variation »
Senanayak Sesh Kumar Karri · Francis Bach · Thomas Pock -
2019 Poster: Towards closing the gap between the theory and practice of SVRG »
Othmane Sebbouh · Nidham Gazagnadou · Samy Jelassi · Francis Bach · Robert Gower -
2019 Poster: An Accelerated Decentralized Stochastic Proximal Algorithm for Finite Sums »
Hadrien Hendrikx · Francis Bach · Laurent Massoulié -
2019 Poster: On Lazy Training in Differentiable Programming »
Lénaïc Chizat · Edouard Oyallon · Francis Bach -
2019 Poster: Implicit Regularization of Discrete Gradient Dynamics in Linear Neural Networks »
Gauthier Gidel · Francis Bach · Simon Lacoste-Julien -
2019 Poster: Massively scalable Sinkhorn distances via the Nyström method »
Jason Altschuler · Francis Bach · Alessandro Rudi · Jonathan Niles-Weed -
2019 Poster: Localized Structured Prediction »
Carlo Ciliberto · Francis Bach · Alessandro Rudi -
2019 Poster: UniXGrad: A Universal, Adaptive Algorithm with Optimal Guarantees for Constrained Optimization »
Ali Kavis · Kfir Y. Levy · Francis Bach · Volkan Cevher -
2019 Spotlight: UniXGrad: A Universal, Adaptive Algorithm with Optimal Guarantees for Constrained Optimization »
Ali Kavis · Kfir Y. Levy · Francis Bach · Volkan Cevher -
2019 Poster: Partially Encrypted Deep Learning using Functional Encryption »
Théo Ryffel · David Pointcheval · Francis Bach · Edouard Dufour-Sans · Romain Gay -
2019 Poster: Globally Convergent Newton Methods for Ill-conditioned Generalized Self-concordant Losses »
Ulysse Marteau-Ferey · Francis Bach · Alessandro Rudi -
2018 Poster: Optimal Algorithms for Non-Smooth Distributed Optimization in Networks »
Kevin Scaman · Francis Bach · Sebastien Bubeck · Laurent Massoulié · Yin Tat Lee -
2018 Poster: Statistical Optimality of Stochastic Gradient Descent on Hard Learning Problems through Multiple Passes »
Loucas Pillaud-Vivien · Alessandro Rudi · Francis Bach -
2018 Oral: Optimal Algorithms for Non-Smooth Distributed Optimization in Networks »
Kevin Scaman · Francis Bach · Sebastien Bubeck · Laurent Massoulié · Yin Tat Lee -
2018 Poster: Relating Leverage Scores and Density using Regularized Christoffel Functions »
Edouard Pauwels · Francis Bach · Jean-Philippe Vert -
2018 Poster: Efficient Algorithms for Non-convex Isotonic Regression through Submodular Optimization »
Francis Bach -
2018 Poster: Rest-Katyusha: Exploiting the Solution's Structure via Scheduled Restart Schemes »
Junqi Tang · Mohammad Golbabaee · Francis Bach · Mike Davies -
2018 Poster: SING: Symbol-to-Instrument Neural Generator »
Alexandre Defossez · Neil Zeghidour · Nicolas Usunier · Leon Bottou · Francis Bach -
2018 Poster: On the Global Convergence of Gradient Descent for Over-parameterized Models using Optimal Transport »
Lénaïc Chizat · Francis Bach -
2017 : Concluding remarks »
Francis Bach · Benjamin Guedj · Pascal Germain -
2017 : Neil Lawrence, Francis Bach and François Laviolette »
Neil Lawrence · Francis Bach · Francois Laviolette -
2017 : Sharp asymptotic and finite-sample rates of convergence of empirical measures in Wasserstein distance »
Francis Bach -
2017 : Overture »
Benjamin Guedj · Francis Bach · Pascal Germain -
2017 Workshop: (Almost) 50 shades of Bayesian Learning: PAC-Bayesian trends and insights »
Benjamin Guedj · Pascal Germain · Francis Bach -
2017 Poster: On Structured Prediction Theory with Calibrated Convex Surrogate Losses »
Anton Osokin · Francis Bach · Simon Lacoste-Julien -
2017 Oral: On Structured Prediction Theory with Calibrated Convex Surrogate Losses »
Anton Osokin · Francis Bach · Simon Lacoste-Julien -
2017 Poster: Nonlinear Acceleration of Stochastic Algorithms »
Damien Scieur · Francis Bach · Alexandre d'Aspremont -
2017 Poster: Integration Methods and Optimization Algorithms »
Damien Scieur · Vincent Roulet · Francis Bach · Alexandre d'Aspremont -
2016 : Francis Bach. Harder, Better, Faster, Stronger Convergence Rates for Least-Squares Regression. »
Francis Bach -
2016 Workshop: OPT 2016: Optimization for Machine Learning »
Suvrit Sra · Francis Bach · Sashank J. Reddi · Niao He -
2016 : Submodular Functions: from Discrete to Continuous Domains »
Francis Bach -
2016 Workshop: Learning in High Dimensions with Structure »
Nikhil Rao · Prateek Jain · Hsiang-Fu Yu · Ming Yuan · Francis Bach -
2016 Poster: Parameter Learning for Log-supermodular Distributions »
Tatiana Shpakova · Francis Bach -
2016 Poster: Regularized Nonlinear Acceleration »
Damien Scieur · Alexandre d'Aspremont · Francis Bach -
2016 Oral: Regularized Nonlinear Acceleration »
Damien Scieur · Alexandre d'Aspremont · Francis Bach -
2016 Poster: Stochastic Variance Reduction Methods for Saddle-Point Problems »
Balamurugan Palaniappan · Francis Bach -
2016 Poster: PAC-Bayesian Theory Meets Bayesian Inference »
Pascal Germain · Francis Bach · Alexandre Lacoste · Simon Lacoste-Julien -
2016 Poster: Stochastic Optimization for Large-scale Optimal Transport »
Aude Genevay · Marco Cuturi · Gabriel Peyré · Francis Bach -
2016 Tutorial: Large-Scale Optimization: Beyond Stochastic Gradient Descent and Convexity »
Suvrit Sra · Francis Bach -
2015 : Sharp Analysis of Random Feature Expansions »
Francis Bach -
2015 : Convergence Rates of Kernel Quadrature Rules »
Francis Bach -
2015 Poster: Rethinking LDA: Moment Matching for Discrete ICA »
Anastasia Podosinnikova · Francis Bach · Simon Lacoste-Julien -
2015 Poster: Spectral Norm Regularization of Orthonormal Representations for Graph Transduction »
Rakesh Shivanna · Bibaswan K Chatterjee · Raman Sankaran · Chiranjib Bhattacharyya · Francis Bach -
2014 Poster: Metric Learning for Temporal Sequence Alignment »
Rémi Lajugie · Damien Garreau · Francis Bach · Sylvain Arlot -
2014 Poster: SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives »
Aaron Defazio · Francis Bach · Simon Lacoste-Julien -
2013 Poster: Non-strongly-convex smooth stochastic approximation with convergence rate O(1/n) »
Francis Bach · Eric Moulines -
2013 Spotlight: Non-strongly-convex smooth stochastic approximation with convergence rate O(1/n) »
Francis Bach · Eric Moulines -
2013 Session: Oral Session 2 »
Francis Bach -
2013 Poster: Convex Relaxations for Permutation Problems »
Fajwel Fogel · Rodolphe Jenatton · Francis Bach · Alexandre d'Aspremont -
2013 Poster: Reflection methods for user-friendly submodular optimization »
Stefanie Jegelka · Francis Bach · Suvrit Sra -
2013 Session: Tutorial Session B »
Francis Bach -
2012 Workshop: Analysis Operator Learning vs. Dictionary Learning: Fraternal Twins in Sparse Modeling »
Martin Kleinsteuber · Francis Bach · Remi Gribonval · John Wright · Simon Hawe -
2012 Poster: Multiple Operator-valued Kernel Learning »
Hachem Kadri · Alain Rakotomamonjy · Francis Bach · philippe preux -
2012 Poster: A Stochastic Gradient Method with an Exponential Convergence
Rate for Finite Training Sets »
Nicolas Le Roux · Mark Schmidt · Francis Bach -
2012 Oral: A Stochastic Gradient Method with an Exponential Convergence
Rate for Finite Training Sets »
Nicolas Le Roux · Mark Schmidt · Francis Bach -
2011 Workshop: Sparse Representation and Low-rank Approximation »
Ameet S Talwalkar · Lester W Mackey · Mehryar Mohri · Michael W Mahoney · Francis Bach · Mike Davies · Remi Gribonval · Guillaume R Obozinski -
2011 Poster: Convergence Rates of Inexact Proximal-Gradient Methods for Convex Optimization »
Mark Schmidt · Nicolas Le Roux · Francis Bach -
2011 Oral: Convergence Rates of Inexact Proximal-Gradient Methods for Convex Optimization »
Mark Schmidt · Nicolas Le Roux · Francis Bach -
2011 Poster: Non-Asymptotic Analysis of Stochastic Approximation Algorithms for Machine Learning »
Francis Bach · Eric Moulines -
2011 Poster: Trace Lasso: a trace norm regularization for correlated designs »
Edouard Grave · Guillaume R Obozinski · Francis Bach -
2011 Spotlight: Non-Asymptotic Analysis of Stochastic Approximation Algorithms for Machine Learning »
Francis Bach · Eric Moulines -
2011 Poster: Shaping Level Sets with Submodular Functions »
Francis Bach -
2010 Workshop: New Directions in Multiple Kernel Learning »
Marius Kloft · Ulrich Rueckert · Cheng Soon Ong · Alain Rakotomamonjy · Soeren Sonnenburg · Francis Bach -
2010 Spotlight: Online Learning for Latent Dirichlet Allocation »
Matthew D. Hoffman · David Blei · Francis Bach -
2010 Poster: Efficient Optimization for Discriminative Latent Class Models »
Armand Joulin · Francis Bach · Jean A Ponce -
2010 Poster: Online Learning for Latent Dirichlet Allocation »
Matthew D. Hoffman · David Blei · Francis Bach -
2010 Oral: Structured sparsity-inducing norms through submodular functions »
Francis Bach -
2010 Poster: Structured sparsity-inducing norms through submodular functions »
Francis Bach -
2010 Poster: Network Flow Algorithms for Structured Sparsity »
Julien Mairal · Rodolphe Jenatton · Guillaume R Obozinski · Francis Bach -
2009 Workshop: Understanding Multiple Kernel Learning Methods »
Brian McFee · Gert Lanckriet · Francis Bach · Nati Srebro -
2009 Poster: Data-driven calibration of linear estimators with minimal penalties »
Sylvain Arlot · Francis Bach -
2009 Poster: Asymptotically Optimal Regularization in Smooth Parametric Models »
Percy Liang · Francis Bach · Guillaume Bouchard · Michael Jordan -
2009 Tutorial: Sparse Methods for Machine Learning: Theory and Algorithms »
Francis Bach -
2008 Poster: Clustered Multi-Task Learning: A Convex Formulation »
Laurent Jacob · Francis Bach · Jean-Philippe Vert -
2008 Poster: Sparse probabilistic projections »
Cedric Archambeau · Francis Bach -
2008 Spotlight: Sparse probabilistic projections »
Cedric Archambeau · Francis Bach -
2008 Spotlight: Clustered Multi-Task Learning: A Convex Formulation »
Laurent Jacob · Francis Bach · Jean-Philippe Vert -
2008 Poster: Exploring Large Feature Spaces with Hierarchical Multiple Kernel Learning »
Francis Bach -
2008 Poster: Kernel Change-point Analysis »
Zaid Harchaoui · Francis Bach · Eric Moulines -
2008 Poster: SDL: Supervised Dictionary Learning »
Julien Mairal · Francis Bach · Jean A Ponce · Guillermo Sapiro · Andrew Zisserman -
2007 Poster: Testing for Homogeneity with Kernel Fisher Discriminant Analysis »
Zaid Harchaoui · Francis Bach · Moulines Eric -
2007 Poster: DIFFRAC: a discriminative and flexible framework for clustering »
Francis Bach · Zaid Harchaoui -
2007 Session: Session 2: Probabilistic Optimization »
Francis Bach -
2006 Poster: Active learning for misspecified generalized linear models »
Francis Bach