Francis R. Bach

Michael I. Jordan, Francis R. Bach, F. Bach, 2003, 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)..

Testing for Homogeneity with Kernel Fisher Discriminant Analysis

Zaïd Harchaoui, Eric Moulines, Francis R. Bach, 2007, NIPS.

Self-concordant analysis for logistic regression pdf

Francis R. Bach, F. Bach, 2009, ArXiv.

Considering Cost Asymmetry in Learning Classifiers

Eric Horvitz, Francis R. Bach, David Heckerman, 2006, J. Mach. Learn. Res..

Approximation bounds for sparse principal component analysis

Alexandre d'Aspremont, Laurent El Ghaoui, Francis R. Bach, 2012, Math. Program..

Signal Processing for Big Data [From the Guest Editors]

Georgios B. Giannakis, Jennifer Neville, Francis R. Bach, 2014, IEEE Signal Process. Mag..

Efficient Optimization for Discriminative Latent Class Models

Jean Ponce, Francis R. Bach, Armand Joulin, 2010, NIPS.

Optimization with Sparsity-Inducing Penalties pdf

Julien Mairal, Francis R. Bach, Guillaume Obozinski, 2011, Found. Trends Mach. Learn..

Learning Determinantal Point Processes in Sublinear Time

Francis R. Bach, Christophe Dupuy, F. Bach, 2016, AISTATS.

Nonlinear Acceleration of Stochastic Algorithms

Alexandre d'Aspremont, Francis R. Bach, Damien Scieur, 2017, NIPS.

Large-Margin Metric Learning for Constrained Partitioning Problems

Francis R. Bach, Sylvain Arlot, Rémi Lajugie, 2014, ICML.

Structured Sparse Principal Component Analysis

Francis R. Bach, Guillaume Obozinski, Rodolphe Jenatton, 2009, AISTATS.

A Stochastic Gradient Method with an Exponential Convergence Rate for Finite Training Sets

Mark W. Schmidt, Nicolas Le Roux, Francis R. Bach, 2012, NIPS.

Spectral Norm Regularization of Orthonormal Representations for Graph Transduction

Francis R. Bach, Chiranjib Bhattacharyya, Raman Sankaran, 2015, NIPS.

A Markovian approach to distributional semantics with application to semantic compositionality

Francis R. Bach, Edouard Grave, Guillaume Obozinski, 2014, COLING.

Learning with Submodular Functions: A Convex Optimization Perspective

Francis R. Bach, F. Bach, 2011, Found. Trends Mach. Learn..

Non-strongly-convex smooth stochastic approximation with convergence rate O(1/n)

Eric Moulines, Francis R. Bach, F. Bach, 2013, NIPS.

Blind One-microphone Speech Separation: A Spectral Learning Approach

Michael I. Jordan, Francis R. Bach, F. Bach, 2004, NIPS.

Multi-task regression using minimal penalties

Francis R. Bach, Sylvain Arlot, Matthieu Solnon, 2011, J. Mach. Learn. Res..

Convergence Rates of Inexact Proximal-Gradient Methods for Convex Optimization

Mark W. Schmidt, Nicolas Le Roux, Francis R. Bach, 2011, NIPS.

Beyond CCA: Moment Matching for Multi-View Models pdf

Francis R. Bach, Simon Lacoste-Julien, Anastasia Podosinnikova, 2016, ICML.

Highly-Smooth Zero-th Order Online Optimization Vianney Perchet pdf

Vianney Perchet, Francis R. Bach, Vianney Perchet, 2016, COLT 2016.

Modèles de Markov cachés pour l'estimation de plusieurs fréquences fondamentales

Michael I. Jordan, Francis R. Bach, 2005, EGC.

Consistency of trace norm minimization

Francis R. Bach, F. Bach, 2007, J. Mach. Learn. Res..

Statistical Convergence of Kernel CCA

Kenji Fukumizu, Arthur Gretton, Francis R. Bach, 2005, NIPS.

Learning Graphical Models with Mercer Kernels

Michael I. Jordan, Francis R. Bach, F. Bach, 2002, NIPS.

Sparse Modeling for Image and Vision Processing pdf

Jean Ponce, Julien Mairal, Francis R. Bach, 2014, Found. Trends Comput. Graph. Vis..

Local Component Analysis pdf

Nicolas Le Roux, Francis R. Bach, 2013, ICLR.

Domain adaptation for sequence labeling using hidden Markov models pdf

Francis R. Bach, Edouard Grave, Guillaume Obozinski, 2013, NIPS 2013.

Local stability and robustness of sparse dictionary learning in the presence of noise pdf

Rémi Gribonval, Francis R. Bach, Rodolphe Jenatton, 2012, ArXiv.

A Tensor-Based Algorithm for High-Order Graph Matching

Jean Ponce, In-So Kweon, Francis R. Bach, 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Rethinking LDA: Moment Matching for Discrete ICA

Francis R. Bach, Simon Lacoste-Julien, Anastasia Podosinnikova, 2015, NIPS.

Non-local sparse models for image restoration

Guillermo Sapiro, Jean Ponce, Andrew Zisserman, 2009, 2009 IEEE 12th International Conference on Computer Vision.

Low-rank matrix factorization with attributes pdf

Francis R. Bach, Theodoros Evgeniou, Jean-Philippe Vert, 2006, ArXiv.

Low-Rank Optimization with Trace Norm Penalty

Bamdev Mishra, Francis R. Bach, Rodolphe Sepulchre, 2011, SIAM J. Optim..

Signal Processing

Zaïd Harchaoui, Eric Moulines, Francis R. Bach, 2013, 2020 27th International Conference on Mixed Design of Integrated Circuits and System (MIXDES).

Highly-Smooth Zero-th Order Online Optimization

Vianney Perchet, Francis R. Bach, Vianney Perchet, 2016, COLT.

Learning graphical models for stationary time series

Michael I. Jordan, Francis R. Bach, F. Bach, 2004, IEEE Transactions on Signal Processing.

Asymptotically Optimal Regularization in Smooth Parametric Models

Michael I. Jordan, Guillaume Bouchard, Francis R. Bach, 2009, NIPS.

Robust Discriminative Clustering with Sparse Regularizers pdf

Francis R. Bach, Nicolas Flammarion, Balamurugan Palaniappan, 2017, J. Mach. Learn. Res..

Learning Spectral Clustering, With Application To Speech Separation

Michael I. Jordan, Francis R. Bach, F. Bach, 2006, J. Mach. Learn. Res..

An online em algorithm in hidden (semi-)Markov models for audio segmentation and clustering

Francis R. Bach, Arshia Cont, Alberto Bietti, 2015, 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Image Classification with Segmentation Graph Kernels

Zaïd Harchaoui, Francis R. Bach, F. Bach, 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

Supervised Dictionary Learning

Guillermo Sapiro, Jean Ponce, Andrew Zisserman, 2008, NIPS.

Primal-dual algorithms for non-negative matrix factorization with the Kullback-Leibler divergence

Francis R. Bach, Felipe Yanez, F. Bach, 2014, 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

More efficiency in multiple kernel learning

Yves Grandvalet, Stéphane Canu, Francis R. Bach, 2007, ICML '07.

Hidden Markov tree models for semantic class induction

Francis R. Bach, Edouard Grave, Guillaume Obozinski, 2013, CoNLL.

Learning with Differentiable Pertubed Optimizers

Francis R. Bach, Jean-Philippe Vert, Marco Cuturi, 2020, NeurIPS.

Tree-dependent Component Analysis

Michael I. Jordan, Francis R. Bach, F. Bach, 2002, UAI.

Thin Junction Trees

Michael I. Jordan, Francis R. Bach, F. Bach, 2001, NIPS.

Large-Margin Metric Learning for Partitioning Problems pdf

Francis R. Bach, Sylvain Arlot, Rémi Lajugie, 2013, ArXiv.

Graph kernels between point clouds

Francis R. Bach, F. Bach, 2007, ICML '08.

Convex Relaxations for Learning Bounded-Treewidth Decomposable Graphs pdf

Francis R. Bach, K. S. Sesh Kumar, F. Bach, 2012, ICML.

Qualitative and Descriptive Topic Extraction from Movie Reviews Using LDA

Francis R. Bach, Christophe Diot, Christophe Dupuy, 2017, MLDM.

Semi-supervised NMF with Time-frequency Annotations for Single-channel Source Separation

Francis R. Bach, Cédric Févotte, Augustin Lefèvre, 2012, ISMIR.

Learning the Structure for Structured Sparsity

Francis R. Bach, Nino Shervashidze, F. Bach, 2014, IEEE Transactions on Signal Processing.

A Path Following Algorithm for Graph Matching

Francis R. Bach, Jean-Philippe Vert, Mikhail Zaslavskiy, 2008, ICISP.

Weakly-Supervised Alignment of Video with Text

Cordelia Schmid, Jean Ponce, Ivan Laptev, 2015, 2015 IEEE International Conference on Computer Vision (ICCV).

Stochastic Composite Least-Squares Regression with Convergence Rate $O(1/n)$

Francis R. Bach, Nicolas Flammarion, F. Bach, 2017, COLT.

On the Consistency of Ordinal Regression Methods

Francis R. Bach, Alexandre Gramfort, Fabian Pedregosa, 2014, J. Mach. Learn. Res..

Integration Methods and Optimization Algorithms

Alexandre d'Aspremont, Francis R. Bach, Vincent Roulet, 2017, NIPS.

On the Equivalence between Quadrature Rules and Random Features pdf

Francis R. Bach, F. Bach, 2015, ArXiv.

Discriminative learned dictionaries for local image analysis

Guillermo Sapiro, Jean Ponce, Andrew Zisserman, 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

From Averaging to Acceleration, There is Only a Step-size

Francis R. Bach, Nicolas Flammarion, F. Bach, 2015, COLT.

Tracking the gradients using the Hessian: A new look at variance reducing stochastic methods

Nicolas Le Roux, Robert M. Gower, Francis R. Bach, 2017, AISTATS.

Guest Editorial: Sparse Coding

Michael Elad, Julien Mairal, Francis R. Bach, 2015, International Journal of Computer Vision.

Predictive low-rank decomposition for kernel methods

Michael I. Jordan, Francis R. Bach, F. Bach, 2005, ICML.

Harder, Better, Faster, Stronger Convergence Rates for Least-Squares Regression pdf

Francis R. Bach, Aymeric Dieuleveut, Nicolas Flammarion, 2016, J. Mach. Learn. Res..

Proximal Methods for Hierarchical Sparse Coding

Julien Mairal, Francis R. Bach, Guillaume Obozinski, 2010, J. Mach. Learn. Res..

Multiple kernel learning, conic duality, and the SMO algorithm

Michael I. Jordan, Gert R. G. Lanckriet, Francis R. Bach, 2004, ICML.

Averaged Least-Mean-Squares: Bias-Variance Trade-offs and Optimal Sampling Distributions

Francis R. Bach, Alexandre Défossez, F. Bach, 2015, AISTATS.

Learning hierarchical and topographic dictionaries with structured sparsity

Julien Mairal, Francis R. Bach, Guillaume Obozinski, 2011, Optical Engineering + Applications.

On the Path to an Ideal ROC Curve: Considering Cost Asymmetry in Learning Classifiers

Eric Horvitz, Francis R. Bach, David Heckerman, 2005, AISTATS.

Learning smoothing models of copy number profiles using breakpoint annotations

Francis R. Bach, Jean-Philippe Vert, Gudrun Schleiermacher, 2013, BMC Bioinformatics.

Online dictionary learning for sparse coding

Guillermo Sapiro, Jean Ponce, Julien Mairal, 2009, ICML '09.

Identifying Groups of Strongly Correlated Variables through Smoothed Ordered Weighted L1-norms

Francis R. Bach, Chiranjib Bhattacharyya, Raman Sankaran, 2017, AISTATS.

Optimal Solutions for Sparse Principal Component Analysis pdf

Alexandre d'Aspremont, Laurent El Ghaoui, Francis R. Bach, 2007, J. Mach. Learn. Res..

Breaking the Curse of Dimensionality with Convex Neural Networks

Francis R. Bach, F. Bach, 2014, J. Mach. Learn. Res..

Convex Relaxations for Subset Selection pdf

Alexandre d'Aspremont, Francis R. Bach, Selin Damla Ahipasaoglu, 2010, ArXiv.

Trace Lasso: a trace norm regularization for correlated designs

Francis R. Bach, Edouard Grave, Guillaume Obozinski, 2011, NIPS.

Multiple Operator-valued Kernel Learning

Philippe Preux, Francis R. Bach, Alain Rakotomamonjy, 2012, NIPS.

Discriminative training of hidden Markov models for multiple pitch tracking [speech processing examples]

Michael I. Jordan, Francis R. Bach, F. Bach, 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..

Consistency of the group Lasso and multiple kernel learning pdf

Francis R. Bach, F. Bach, 2007, J. Mach. Learn. Res..

Sampling from Arbitrary Functions via PSD Models pdf

Alessandro Rudi, Francis R. Bach, Ulysse Marteau-Ferey, 2021, AISTATS.