ML Anthology

Bach, Francis R.

98 publications

TMLR 2025 Optimizing Estimators of Squared Calibration Errors in Classification Sebastian Gregor Gruber, Francis R. Bach
NeurIPS 2023 Differentiable Clustering with Perturbed Spanning Forests Lawrence Stewart, Francis R. Bach, Felipe Llinares-Lopez, Quentin Berthet
NeurIPS 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 Antonio Ribeiro, Dave Zachariah, Francis R. Bach, Thomas Schön
NeurIPS 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 Asynchronous SGD Beats Minibatch SGD Under Arbitrary Delays Konstantin Mishchenko, Francis R. Bach, Mathieu Even, Blake E Woodworth
NeurIPS 2022 Fast Stochastic Composite Minimization and an Accelerated Frank-Wolfe Algorithm Under Parallelization Benjamin Dubois-Taine, Francis R. Bach, Quentin Berthet, Adrien Taylor
NeurIPS 2022 On the Theoretical Properties of Noise Correlation in Stochastic Optimization Aurelien Lucchi, Frank Proske, Antonio Orvieto, Francis R. Bach, Hans Kersting
NeurIPS 2022 Variational Inference via Wasserstein Gradient Flows Marc Lambert, Sinho Chewi, Francis R. Bach, Silvère Bonnabel, Philippe Rigollet
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 Taylor
NeurIPS 2021 Overcoming the Curse of Dimensionality with Laplacian Regularization in Semi-Supervised Learning Vivien Cabannes, Loucas Pillaud-Vivien, Francis R. Bach, Alessandro Rudi
NeurIPS 2020 Batch Normalization Provably Avoids Ranks Collapse for Randomly Initialised Deep Networks Hadi Daneshmand, Jonas Kohler, Francis R. Bach, Thomas Hofmann, Aurelien Lucchi
NeurIPS 2020 Dual-Free Stochastic Decentralized Optimization with Variance Reduction Hadrien Hendrikx, Francis R. Bach, Laurent Massoulié
NeurIPS 2020 Learning with Differentiable Pertubed Optimizers Quentin Berthet, Mathieu Blondel, Olivier Teboul, Marco Cuturi, Jean-Philippe Vert, Francis R. Bach
IJCAI 2020 Learning with Subquadratic Regularization : A Primal-Dual Approach Raman Sankaran, Francis R. Bach, Chiranjib Bhattacharyya
NeurIPS 2020 Non-Parametric Models for Non-Negative Functions Ulysse Marteau-Ferey, Francis R. Bach, Alessandro Rudi
NeurIPS 2020 Tight Nonparametric Convergence Rates for Stochastic Gradient Descent Under the Noiseless Linear Model Raphaël Berthier, Francis R. Bach, Pierre Gaillard
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
COLT 2018 Averaging Stochastic Gradient Descent on Riemannian Manifolds Nilesh Tripuraneni, Nicolas Flammarion, Francis R. Bach, Michael I. Jordan
AISTATS 2018 Combinatorial Penalties: Which Structures Are Preserved by Convex Relaxations? Marwa El Halabi, Francis R. Bach, Volkan Cevher
UAI 2018 Constant Step Size Stochastic Gradient Descent for Probabilistic Modeling Dmitry Babichev, Francis R. Bach
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
COLT 2018 Exponential Convergence of Testing Error for Stochastic Gradient Methods Loucas Pillaud-Vivien, Alessandro Rudi, Francis R. Bach
AISTATS 2018 Learning Determinantal Point Processes in Sublinear Time Christophe Dupuy, 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
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 2017 Identifying Groups of Strongly Correlated Variables Through Smoothed Ordered Weighted L1-Norms Raman Sankaran, Francis R. Bach, Chiranjib Bhattacharyya
COLT 2016 Highly-Smooth Zero-Th Order Online Optimization Francis R. Bach, Vianney Perchet
AISTATS 2015 Averaged Least-Mean-Squares: Bias-Variance Trade-Offs and Optimal Sampling Distributions Alexandre Défossez, Francis R. Bach
COLT 2015 From Averaging to Acceleration, There Is Only a Step-Size Nicolas Flammarion, Francis R. Bach
AISTATS 2015 Sequential Kernel Herding: Frank-Wolfe Optimization for Particle Filtering Simon Lacoste-Julien, Fredrik Lindsten, Francis R. Bach
ECCV 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
FnTML 2013 Learning with Submodular Functions: A Convex Optimization Perspective Francis R. Bach
ICLR 2013 Local Component Analysis Nicolas Le Roux, Francis R. Bach
COLT 2013 Sharp Analysis of Low-Rank Kernel Matrix Approximations Francis R. Bach
ICML 2012 A Convex Relaxation for Weakly Supervised Classifiers Armand Joulin, Francis R. Bach
NeurIPS 2012 A Stochastic Gradient Method with an Exponential Convergence _Rate for Finite Training Sets Nicolas L. Roux, Mark Schmidt, Francis R. Bach
CVPR 2012 Multi-Class Cosegmentation Armand Joulin, Francis R. Bach, Jean Ponce
NeurIPS 2012 Multiple Operator-Valued Kernel Learning Hachem Kadri, Alain Rakotomamonjy, Philippe Preux, Francis R. Bach
ICML 2012 On the Equivalence Between Herding and Conditional Gradient Algorithms Francis R. Bach, Simon Lacoste-Julien, Guillaume Obozinski
FnTML 2012 Optimization with Sparsity-Inducing Penalties Francis R. Bach, Rodolphe Jenatton, Julien Mairal, Guillaume Obozinski
ICCV 2011 Ask the Locals: Multi-Way Local Pooling for Image Recognition Y-Lan Boureau, Nicolas Le Roux, Francis R. Bach, Jean Ponce, Yann LeCun
ICML 2011 Clusterpath: An Algorithm for Clustering Using Convex Fusion Penalties Toby Hocking, Jean-Philippe Vert, Francis R. Bach, Armand Joulin
NeurIPS 2011 Convergence Rates of Inexact Proximal-Gradient Methods for Convex Optimization Mark Schmidt, Nicolas L. Roux, Francis R. Bach
NeurIPS 2011 Non-Asymptotic Analysis of Stochastic Approximation Algorithms for Machine Learning Eric Moulines, Francis R. Bach
NeurIPS 2011 Shaping Level Sets with Submodular Functions Francis R. Bach
CVPR 2011 Sparse Image Representation with Epitomes Louise Benoît, Julien Mairal, Francis R. Bach, Jean Ponce
NeurIPS 2011 Trace Lasso: A Trace Norm Regularization for Correlated Designs Edouard Grave, Guillaume R. Obozinski, Francis R. Bach
CVPR 2010 Discriminative Clustering for Image Co-Segmentation Armand Joulin, Francis R. Bach, Jean Ponce
NeurIPS 2010 Efficient Optimization for Discriminative Latent Class Models Armand Joulin, Jean Ponce, Francis R. Bach
CVPR 2010 Learning Mid-Level Features for Recognition Y-Lan Boureau, Francis R. Bach, Yann LeCun, Jean Ponce
ECML-PKDD 2010 Many-to-Many Graph Matching: A Continuous Relaxation Approach Mikhail Zaslavskiy, Francis R. Bach, Jean-Philippe Vert
NeurIPS 2010 Network Flow Algorithms for Structured Sparsity Julien Mairal, Rodolphe Jenatton, Francis R. Bach, Guillaume R. Obozinski
NeurIPS 2010 Online Learning for Latent Dirichlet Allocation Matthew Hoffman, Francis R. Bach, David M. Blei
ICML 2010 Proximal Methods for Sparse Hierarchical Dictionary Learning Rodolphe Jenatton, Julien Mairal, Guillaume Obozinski, Francis R. Bach
NeurIPS 2010 Structured Sparsity-Inducing Norms Through Submodular Functions Francis R. Bach
CVPR 2009 A Tensor-Based Algorithm for High-Order Graph Matching Olivier Duchenne, Francis R. Bach, In-So Kweon, Jean Ponce
NeurIPS 2009 Asymptotically Optimal Regularization in Smooth Parametric Models Percy Liang, Guillaume Bouchard, Francis R. Bach, Michael I. Jordan
ICCV 2009 Automatic Annotation of Human Actions in Video Olivier Duchenne, Ivan Laptev, Josef Sivic, Francis R. Bach, Jean Ponce
NeurIPS 2009 Data-Driven Calibration of Linear Estimators with Minimal Penalties Sylvain Arlot, Francis R. Bach
ICCV 2009 Non-Local Sparse Models for Image Restoration Julien Mairal, Francis R. Bach, Jean Ponce, Guillermo Sapiro, Andrew Zisserman
ICML 2009 Online Dictionary Learning for Sparse Coding Julien Mairal, Francis R. Bach, Jean Ponce, Guillermo Sapiro
ICML 2008 Bolasso: Model Consistent Lasso Estimation Through the Bootstrap Francis R. Bach
NeurIPS 2008 Clustered Multi-Task Learning: A Convex Formulation Laurent Jacob, Jean-philippe Vert, Francis R. Bach
JMLR 2008 Consistency of Trace Norm Minimization Francis R. Bach
JMLR 2008 Consistency of the Group Lasso and Multiple Kernel Learning Francis R. Bach
CVPR 2008 Discriminative Learned Dictionaries for Local Image Analysis Julien Mairal, Francis R. Bach, Jean Ponce, Guillermo Sapiro, Andrew Zisserman
ECCV 2008 Discriminative Sparse Image Models for Class-Specific Edge Detection and Image Interpretation Julien Mairal, Marius Leordeanu, Francis R. Bach, Martial Hebert, Jean Ponce
NeurIPS 2008 Exploring Large Feature Spaces with Hierarchical Multiple Kernel Learning Francis R. Bach
ICML 2008 Graph Kernels Between Point Clouds Francis R. Bach
NeurIPS 2008 Kernel Change-Point Analysis Zaïd Harchaoui, Eric Moulines, Francis R. Bach
JMLR 2008 SimpleMKL Alain Rakotomamonjy, Francis R. Bach, Stéphane Canu, Yves Grandvalet
NeurIPS 2008 Sparse Probabilistic Projections Cédric Archambeau, Francis R. Bach
NeurIPS 2008 Supervised Dictionary Learning Julien Mairal, Jean Ponce, Guillermo Sapiro, Andrew Zisserman, Francis R. Bach
NeurIPS 2007 DIFFRAC: A Discriminative and Flexible Framework for Clustering Francis R. Bach, Zaïd Harchaoui
ICML 2007 Full Regularization Path for Sparse Principal Component Analysis Alexandre d'Aspremont, Francis R. Bach, Laurent El Ghaoui
CVPR 2007 Image Classification with Segmentation Graph Kernels Zaïd Harchaoui, Francis R. Bach
ICML 2007 More Efficiency in Multiple Kernel Learning Alain Rakotomamonjy, Francis R. Bach, Stéphane Canu, Yves Grandvalet
JMLR 2007 Statistical Consistency of Kernel Canonical Correlation Analysis Kenji Fukumizu, Francis R. Bach, Arthur Gretton
NeurIPS 2007 Testing for Homogeneity with Kernel Fisher Discriminant Analysis Moulines Eric, Francis R. Bach, Zaïd Harchaoui
NeurIPS 2006 Active Learning for Misspecified Generalized Linear Models Francis R. Bach
JMLR 2006 Considering Cost Asymmetry in Learning Classifiers Francis R. Bach, David Heckerman, Eric Horvitz
JMLR 2006 Learning Spectral Clustering, with Application to Speech Separation Francis R. Bach, Michael I. Jordan
ICML 2005 Predictive Low-Rank Decomposition for Kernel Methods Francis R. Bach, Michael I. Jordan
NeurIPS 2005 Statistical Convergence of Kernel CCA Kenji Fukumizu, Arthur Gretton, Francis R. Bach
NeurIPS 2004 Blind One-Microphone Speech Separation: A Spectral Learning Approach Francis R. Bach, Michael I. Jordan
NeurIPS 2004 Computing Regularization Paths for Learning Multiple Kernels Francis R. Bach, Romain Thibaux, Michael I. Jordan
JMLR 2004 Dimensionality Reduction for Supervised Learning with Reproducing Kernel Hilbert Spaces Kenji Fukumizu, Francis R. Bach, Michael I. Jordan
ICML 2004 Multiple Kernel Learning, Conic Duality, and the SMO Algorithm Francis R. Bach, Gert R. G. Lanckriet, Michael I. Jordan
JMLR 2003 Beyond Independent Components: Trees and Clusters Francis R. Bach, Michael I. Jordan
NeurIPS 2003 Kernel Dimensionality Reduction for Supervised Learning Kenji Fukumizu, Francis R. Bach, Michael I. Jordan
NeurIPS 2003 Learning Spectral Clustering Francis R. Bach, Michael I. Jordan
JMLR 2002 Kernel Independent Component Analysis (Kernel Machines Section) Francis R. Bach, Michael I. Jordan
NeurIPS 2002 Learning Graphical Models with Mercer Kernels Francis R. Bach, Michael I. Jordan
UAI 2002 Tree-Dependent Component Analysis Francis R. Bach, Michael I. Jordan
NeurIPS 2001 Thin Junction Trees Francis R. Bach, Michael I. Jordan