Francis R. Bach

Francis R. Bach, Michael I. Jordan: Tree-dependent Component Analysis. CoRR abs/1301.0554 (2013)

Rémi Lajugie, Sylvain Arlot, Francis Bach: Large-Margin Metric Learning for Partitioning Problems. CoRR abs/1303.1280 (2013)

Francis Bach: Adaptivity of averaged stochastic gradient descent to local strong convexity for logistic regression. CoRR abs/1303.6149 (2013)

Francis R. Bach, Rodolphe Jenatton, Julien Mairal, Guillaume Obozinski: Optimization with Sparsity-Inducing Penalties. Foundations and Trends in Machine Learning 4(1): 1-106 (2012)

Julien Mairal, Francis Bach, Jean Ponce: Task-Driven Dictionary Learning. IEEE Trans. Pattern Anal. Mach. Intell. 34(4): 791-804 (2012)

Rodolphe Jenatton, Alexandre Gramfort, Vincent Michel, Guillaume Obozinski, Evelyn Eger, Francis Bach, Bertrand Thirion: Multiscale Mining of fMRI Data with Hierarchical Structured Sparsity. SIAM J. Imaging Sciences 5(3): 835-856 (2012)

Armand Joulin, Francis Bach, Jean Ponce: Multi-class cosegmentation. CVPR 2012: 542-549

Francis Bach, Simon Lacoste-Julien, Guillaume Obozinski: On the Equivalence between Herding and Conditional Gradient Algorithms. ICML 2012

Armand Joulin, Francis Bach: A convex relaxation for weakly supervised classifiers. ICML 2012

Francis Bach: Structured Sparsity and Convex Optimization. ICPRAM (1) 2012

Augustin Lefevre, Francis Bach, Cédric Févotte: Semi-supervised NMF with Time-frequency Annotations for Single-channel Source Separation. ISMIR 2012: 115-120

Hachem Kadri, Alain Rakotomamonjy, Francis Bach, Philippe Preux: Multiple Operator-valued Kernel Learning. NIPS 2012: 2438-2446

Nicolas Le Roux, Mark W. Schmidt, Francis Bach: A Stochastic Gradient Method with an Exponential Convergence Rate for Finite Training Sets. NIPS 2012: 2672-2680

Nicolas Le Roux, Mark W. Schmidt, Francis Bach: A Stochastic Gradient Method with an Exponential Convergence Rate for Strongly-Convex Optimization with Finite Training Sets. CoRR abs/1202.6258 (2012)

Hachem Kadri, Alain Rakotomamonjy, Francis Bach, Philippe Preux: Multiple Operator-valued Kernel Learning. CoRR abs/1203.1596 (2012)

Francis Bach, Simon Lacoste-Julien, Guillaume Obozinski: On the Equivalence between Herding and Conditional Gradient Algorithms. CoRR abs/1203.4523 (2012)

Guillaume Obozinski, Francis Bach: Convex Relaxation for Combinatorial Penalties. CoRR abs/1205.1240 (2012)

Francis Bach: Sharp analysis of low-rank kernel matrix approximations. CoRR abs/1208.2015 (2012)

Rodolphe Jenatton, Rémi Gribonval, Francis Bach: Local stability and robustness of sparse dictionary learning in the presence of noise. CoRR abs/1210.0685 (2012)

Francis Bach: Duality between subgradient and conditional gradient methods. CoRR abs/1211.6302 (2012)

Simon Lacoste-Julien, Mark W. Schmidt, Francis Bach: A simpler approach to obtaining an O(1/t) convergence rate for the projected stochastic subgradient method. CoRR abs/1212.2002 (2012)

K. S. Sesh Kumar, Francis Bach: Convex Relaxations for Learning Bounded Treewidth Decomposable Graphs. CoRR abs/1212.2573 (2012)

Rodolphe Jenatton, Julien Mairal, Guillaume Obozinski, Francis Bach: Proximal Methods for Hierarchical Sparse Coding. Journal of Machine Learning Research 12: 2297-2334 (2011)

Julien Mairal, Rodolphe Jenatton, Guillaume Obozinski, Francis Bach: Convex and Network Flow Optimization for Structured Sparsity. Journal of Machine Learning Research 12: 2681-2720 (2011)

Rodolphe Jenatton, Jean-Yves Audibert, Francis Bach: Structured Variable Selection with Sparsity-Inducing Norms. Journal of Machine Learning Research 12: 2777-2824 (2011)

Alexandre d'Aspremont, Francis R. Bach, Inderjit S. Dhillon, Bin Yu: Preface. Math. Program. 127(1): 1-2 (2011)

Olivier Duchenne, Francis Bach, In-So Kweon, Jean Ponce: A Tensor-Based Algorithm for High-Order Graph Matching. IEEE Trans. Pattern Anal. Mach. Intell. 33(12): 2383-2395 (2011)

Louise Benoît, Julien Mairal, Francis Bach, Jean Ponce: Sparse image representation with epitomes. CVPR 2011: 2913-2920

Augustin Lefevre, Francis Bach, Cédric Févotte: Itakura-Saito nonnegative matrix factorization with group sparsity. ICASSP 2011: 21-24

Y-Lan Boureau, Nicolas Le Roux, Francis Bach, Jean Ponce, Yann LeCun: Ask the locals: Multi-way local pooling for image recognition. ICCV 2011: 2651-2658

Toby Hocking, Jean-Philippe Vert, Francis Bach, Armand Joulin: Clusterpath: an Algorithm for Clustering using Convex Fusion Penalties. ICML 2011: 745-752

Francis Bach: Shaping Level Sets with Submodular Functions. NIPS 2011: 10-18

Francis Bach, Eric Moulines: Non-Asymptotic Analysis of Stochastic Approximation Algorithms for Machine Learning. NIPS 2011: 451-459

Mark W. Schmidt, Nicolas Le Roux, Francis Bach: Convergence Rates of Inexact Proximal-Gradient Methods for Convex Optimization. NIPS 2011: 1458-1466

Edouard Grave, Guillaume Obozinski, Francis Bach: Trace Lasso: a trace norm regularization for correlated designs. NIPS 2011: 2187-2195

Augustin Lefevre, Francis Bach, Cédric Févotte: Online algorithms for nonnegative matrix factorization with the Itakura-Saito divergence. WASPAA 2011: 313-316

Julien Mairal, Rodolphe Jenatton, Guillaume Obozinski, Francis Bach: Convex and Network Flow Optimization for Structured Sparsity. CoRR abs/1104.1872 (2011)

Francis Bach, Rodolphe Jenatton, Julien Mairal, Guillaume Obozinski: Optimization with Sparsity-Inducing Penalties. CoRR abs/1108.0775 (2011)

Nicolas Le Roux, Francis Bach: Local Component Analysis. CoRR abs/1109.0093 (2011)

Edouard Grave, Guillaume Obozinski, Francis R. Bach: Trace Lasso: a trace norm regularization for correlated designs. CoRR abs/1109.1990 (2011)

Francis Bach, Rodolphe Jenatton, Julien Mairal, Guillaume Obozinski: Structured sparsity through convex optimization. CoRR abs/1109.2397 (2011)

Mark W. Schmidt, Nicolas Le Roux, Francis Bach: Convergence Rates of Inexact Proximal-Gradient Methods for Convex Optimization. CoRR abs/1109.2415 (2011)

Florent Couzinie-Devy, Julien Mairal, Francis Bach, Jean Ponce: Dictionary Learning for Deblurring and Digital Zoom. CoRR abs/1110.0957 (2011)

Louise Benoît, Julien Mairal, Francis Bach, Jean Ponce: Sparse Image Representation with Epitomes. CoRR abs/1110.2855 (2011)

Julien Mairal, Rodolphe Jenatton, Guillaume Obozinski, Francis Bach: Learning Hierarchical and Topographic Dictionaries with Structured Sparsity. CoRR abs/1110.4481 (2011)

Francis Bach: Learning with Submodular Functions: A Convex Optimization Perspective. CoRR abs/1111.6453 (2011)

B. Mishra, Gilles Meyer, Francis Bach, Rodolphe Sepulchre: Low-rank optimization with trace norm penalty. CoRR abs/1112.2318 (2011)

Rodolphe Jenatton, Guillaume Obozinski, Francis Bach: Structured Sparse Principal Component Analysis. Journal of Machine Learning Research - Proceedings Track 9: 366-373 (2010)

Julien Mairal, Francis Bach, Jean Ponce, Guillermo Sapiro: Online Learning for Matrix Factorization and Sparse Coding. Journal of Machine Learning Research 11: 19-60 (2010)

Michel Journée, Francis R. Bach, Pierre-Antoine Absil, Rodolphe Sepulchre: Low-Rank Optimization on the Cone of Positive Semidefinite Matrices. SIAM Journal on Optimization 20(5): 2327-2351 (2010)

Armand Joulin, Francis R. Bach, Jean Ponce: Discriminative clustering for image co-segmentation. CVPR 2010: 1943-1950

Y-Lan Boureau, Francis Bach, Yann LeCun, Jean Ponce: Learning mid-level features for recognition. CVPR 2010: 2559-2566

Rodolphe Jenatton, Julien Mairal, Guillaume Obozinski, Francis Bach: Proximal Methods for Sparse Hierarchical Dictionary Learning. ICML 2010: 487-494

Francis R. Bach: Structured sparsity-inducing norms through submodular functions. NIPS 2010: 118-126

Matthew D. Hoffman, David M. Blei, Francis R. Bach: Online Learning for Latent Dirichlet Allocation. NIPS 2010: 856-864

Armand Joulin, Francis R. Bach, Jean Ponce: Efficient Optimization for Discriminative Latent Class Models. NIPS 2010: 1045-1053

Julien Mairal, Rodolphe Jenatton, Guillaume Obozinski, Francis R. Bach: Network Flow Algorithms for Structured Sparsity. NIPS 2010: 1558-1566

Mikhail Zaslavskiy, Francis Bach, Jean-Philippe Vert: Many-to-Many Graph Matching: A Continuous Relaxation Approach. ECML/PKDD (3) 2010: 515-530

Mikhail Zaslavskiy, Francis Bach, Jean-Philippe Vert: Many-to-Many Graph Matching: a Continuous Relaxation Approach. CoRR abs/1004.4965 (2010)

Francis Bach, Selin Damla Ahipasaoglu, Alexandre d'Aspremont: Convex Relaxations for Subset Selection. CoRR abs/1006.3601 (2010)

Francis Bach: Structured sparsity-inducing norms through submodular functions. CoRR abs/1008.4220 (2010)

Julien Mairal, Rodolphe Jenatton, Guillaume Obozinski, Francis Bach: Network Flow Algorithms for Structured Sparsity. CoRR abs/1008.5209 (2010)

Francis Bach: Convex Analysis and Optimization with Submodular Functions: a Tutorial. CoRR abs/1010.4207 (2010)

Francis Bach: Shaping Level Sets with Submodular Functions. CoRR abs/1012.1501 (2010)

Mikhail Zaslavskiy, Francis R. Bach, Jean-Philippe Vert: Global alignment of protein-protein interaction networks by graph matching methods. Bioinformatics 25(12) (2009)

Jacob Abernethy, Francis Bach, Theodoros Evgeniou, Jean-Philippe Vert: A New Approach to Collaborative Filtering: Operator Estimation with Spectral Regularization. Journal of Machine Learning Research 10: 803-826 (2009)

Mikhail Zaslavskiy, Francis R. Bach, Jean-Philippe Vert: A Path Following Algorithm for the Graph Matching Problem. IEEE Trans. Pattern Anal. Mach. Intell. 31(12): 2227-2242 (2009)

Olivier Duchenne, Francis R. Bach, In-So Kweon, Jean Ponce: A tensor-based algorithm for high-order graph matching. CVPR 2009: 1980-1987

Olivier Duchenne, Ivan Laptev, Josef Sivic, Francis Bach, Jean Ponce: Automatic annotation of human actions in video. ICCV 2009: 1491-1498

Julien Mairal, Francis Bach, Jean Ponce, Guillermo Sapiro, Andrew Zisserman: Non-local sparse models for image restoration. ICCV 2009: 2272-2279

Julien Mairal, Francis Bach, Jean Ponce, Guillermo Sapiro: Online dictionary learning for sparse coding. ICML 2009: 87

Sylvain Arlot, Francis R. Bach: Data-driven calibration of linear estimators with minimal penalties. NIPS 2009: 46-54

Percy Liang, Francis R. Bach, Guillaume Bouchard, Michael I. Jordan: Asymptotically Optimal Regularization in Smooth Parametric Models. NIPS 2009: 1132-1140

Francis Bach: Model-Consistent Sparse Estimation through the Bootstrap. CoRR abs/0901.3202 (2009)

Julien Mairal, Francis R. Bach, Jean Ponce, Guillermo Sapiro: Online Learning for Matrix Factorization and Sparse Coding. CoRR abs/0908.0050 (2009)

Francis Bach: High-Dimensional Non-Linear Variable Selection through Hierarchical Kernel Learning. CoRR abs/0909.0844 (2009)

Francis Bach: Self-concordant analysis for logistic regression. CoRR abs/0910.4627 (2009)

Francis R. Bach: Consistency of Trace Norm Minimization. Journal of Machine Learning Research 9: 1019-1048 (2008)

Francis R. Bach: Consistency of the Group Lasso and Multiple Kernel Learning. Journal of Machine Learning Research 9: 1179-1225 (2008)

Alexandre d'Aspremont, Francis Bach, Laurent El Ghaoui: Optimal Solutions for Sparse Principal Component Analysis. Journal of Machine Learning Research 9: 1269-1294 (2008)

Julien Mairal, Francis Bach, Jean Ponce, Guillermo Sapiro, Andrew Zisserman: Discriminative learned dictionaries for local image analysis. CVPR 2008

Julien Mairal, Marius Leordeanu, Francis Bach, Martial Hebert, Jean Ponce: Discriminative Sparse Image Models for Class-Specific Edge Detection and Image Interpretation. ECCV (3) 2008: 43-56

Mikhail Zaslavskiy, Francis Bach, Jean-Philippe Vert: A Path Following Algorithm for Graph Matching. ICISP 2008: 329-337

Francis R. Bach: Graph kernels between point clouds. ICML 2008: 25-32

Francis R. Bach: Bolasso: model consistent Lasso estimation through the bootstrap. ICML 2008: 33-40

Cédric Archambeau, Francis Bach: Sparse probabilistic projections. NIPS 2008: 73-80

Francis Bach: Exploring Large Feature Spaces with Hierarchical Multiple Kernel Learning. NIPS 2008: 105-112

Zaïd Harchaoui, Francis Bach, Eric Moulines: Kernel Change-point Analysis. NIPS 2008: 609-616

Laurent Jacob, Francis Bach, Jean-Philippe Vert: Clustered Multi-Task Learning: A Convex Formulation. NIPS 2008: 745-752

Julien Mairal, Francis Bach, Jean Ponce, Guillermo Sapiro, Andrew Zisserman: Supervised Dictionary Learning. NIPS 2008: 1033-1040

Mikhail Zaslavskiy, Francis Bach, Jean-Philippe Vert: Path following algorithm for the graph matching problem. CoRR abs/0801.3654 (2008)

Francis Bach, Jacob Abernethy, Jean-Philippe Vert, Theodoros Evgeniou: A New Approach to Collaborative Filtering: Operator Estimation with Spectral Regularization. CoRR abs/0802.1430 (2008)

Francis Bach: Bolasso: model consistent Lasso estimation through the bootstrap. CoRR abs/0804.1302 (2008)

Francis Bach: Exploring Large Feature Spaces with Hierarchical Multiple Kernel Learning. CoRR abs/0809.1493 (2008)

Laurent Jacob, Francis Bach, Jean-Philippe Vert: Clustered Multi-Task Learning: A Convex Formulation. CoRR abs/0809.2085 (2008)

Julien Mairal, Francis Bach, Jean Ponce, Guillermo Sapiro, Andrew Zisserman: Supervised Dictionary Learning. CoRR abs/0809.3083 (2008)

Francis Bach, Julien Mairal, Jean Ponce: Convex Sparse Matrix Factorizations. CoRR abs/0812.1869 (2008)

Yoshihiro Yamanishi, Francis Bach, Jean-Philippe Vert: Glycan classification with tree kernels. Bioinformatics 23(10): 1211-1216 (2007)

Kenji Fukumizu, Francis R. Bach, Arthur Gretton: Statistical Consistency of Kernel Canonical Correlation Analysis. Journal of Machine Learning Research 8: 361-383 (2007)

Jérôme Louradour, Khalid Daoudi, Francis R. Bach: Feature Space Mahalanobis Sequence Kernels: Application to SVM Speaker Verification. IEEE Transactions on Audio, Speech & Language Processing 15(8): 2465-2475 (2007)

Zaïd Harchaoui, Francis Bach: Image Classification with Segmentation Graph Kernels. CVPR 2007

Alexandre d'Aspremont, Francis R. Bach, Laurent El Ghaoui: Full regularization path for sparse principal component analysis. ICML 2007: 177-184

Alain Rakotomamonjy, Francis Bach, Stéphane Canu, Yves Grandvalet: More efficiency in multiple kernel learning. ICML 2007: 775-782

Francis Bach, Zaïd Harchaoui: DIFFRAC: a discriminative and flexible framework for clustering. NIPS 2007

Zaïd Harchaoui, Francis Bach, Eric Moulines: Testing for Homogeneity with Kernel Fisher Discriminant Analysis. NIPS 2007

Alexandre d'Aspremont, Francis R. Bach, Laurent El Ghaoui: Optimal Solutions for Sparse Principal Component Analysis. CoRR abs/0707.0705 (2007)

Francis Bach: Consistency of the group Lasso and multiple kernel learning. CoRR abs/0707.3390 (2007)

Francis Bach: Consistency of trace norm minimization. CoRR abs/0710.2848 (2007)

Francis Bach: Graph kernels between point clouds. CoRR abs/0712.3402 (2007)

Francis R. Bach, David Heckerman, Eric Horvitz: Considering Cost Asymmetry in Learning Classifiers. Journal of Machine Learning Research 7: 1713-1741 (2006)

Francis R. Bach, Michael I. Jordan: Learning Spectral Clustering, With Application To Speech Separation. Journal of Machine Learning Research 7: 1963-2001 (2006)

Francis R. Bach: Active learning for misspecified generalized linear models. NIPS 2006: 65-72

Jacob Abernethy, Francis Bach, Theodoros Evgeniou, Jean-Philippe Vert: Low-rank matrix factorization with attributes. CoRR abs/cs/0611124 (2006)

Francis R. Bach, Michael I. Jordan: Predictive low-rank decomposition for kernel methods. ICML 2005: 33-40

Kenji Fukumizu, Francis R. Bach, Arthur Gretton: Statistical Convergence of Kernel CCA. NIPS 2005

Kenji Fukumizu, Francis R. Bach, Michael I. Jordan: Dimensionality Reduction for Supervised Learning with Reproducing Kernel Hilbert Spaces. Journal of Machine Learning Research 5: 73-99 (2004)

Francis R. Bach, Michael I. Jordan: Learning graphical models for stationary time series. IEEE Transactions on Signal Processing 52(8): 2189-2199 (2004)

Francis R. Bach, Gert R. G. Lanckriet, Michael I. Jordan: Multiple kernel learning, conic duality, and the SMO algorithm. ICML 2004

Francis R. Bach, Michael I. Jordan: Blind One-microphone Speech Separation: A Spectral Learning Approach. NIPS 2004

Francis R. Bach, Romain Thibaux, Michael I. Jordan: Computing regularization paths for learning multiple kernels. NIPS 2004

Francis R. Bach, Michael I. Jordan: Beyond Independent Components: Trees and Clusters. Journal of Machine Learning Research 4: 1205-1233 (2003)

Francis R. Bach, Michael I. Jordan: Learning Spectral Clustering. NIPS 2003

Kenji Fukumizu, Francis R. Bach, Michael I. Jordan: Kernel Dimensionality Reduction for Supervised Learning. NIPS 2003

Francis R. Bach, Michael I. Jordan: Kernel Independent Component Analysis. Journal of Machine Learning Research 3: 1-48 (2002)

Francis R. Bach, Michael I. Jordan: Learning Graphical Models with Mercer Kernels. NIPS 2002: 1009-1016

Francis R. Bach, Michael I. Jordan: Tree-dependent Component Analysis. UAI 2002: 36-44

Francis R. Bach, Michael I. Jordan: Thin Junction Trees. NIPS 2001: 569-576