1. Recherche
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hal-00796921v1  Communication dans un congrès
Rémi Lajugie, Sylvain Arlot, Francis Bach. Large-Margin Metric Learning for Constrained Partitioning Problems
Proceedings of The 31st International Conference on Machine Learning, Jun 2014, Beijing, China
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hal-00723365v3  Communication dans un congrès
Francis Bach. Sharp analysis of low-rank kernel matrix approximations
International Conference on Learning Theory (COLT), 2013, United States. 2013
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hal-01123492v1  Pré-publication, Document de travail
K. S. Sesh Kumar, Alvaro Barbero, Stefanie Jegelka, Suvrit Sra, Francis Bach. Convex Optimization for Parallel Energy Minimization
2015
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hal-00426227v1  Pré-publication, Document de travail
Francis Bach. Self-concordant analysis for logistic regression
2009
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hal-00465916v1  Pré-publication, Document de travail
Mikhail Zaslavskiy, Francis Bach, Jean-Philippe Vert. Many-to-Many Graph Matching: a Continuous Relaxation Approach
19. 2009
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hal-00414774v2  Communication dans un congrès
Sylvain Arlot, Francis Bach. Data-driven calibration of linear estimators with minimal penalties
NIPS 2009 - Advances in Neural Information Processing Systems, Dec 2009, Vancouver, Canada. 22, pp.46--54, 2009
inria-00386560v1  Communication dans un congrès
Francis Bach. Apprentissage par noyaux multiples
41èmes Journées de Statistique, SFdS, Bordeaux, 2009, Bordeaux, France, France. 2009
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hal-00905258v1  Communication dans un congrès
Stefanie Jegelka, Francis Bach, Suvrit Sra. Reflection methods for user-friendly submodular optimization
NIPS 2013 - Neural Information Processing Systems, Dec 2013, Lake Tahoe, Nevada, United States. 2013
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hal-01472867v1  Pré-publication, Document de travail
Nicolas Flammarion, Francis Bach. Stochastic Composite Least-Squares Regression with convergence rate O(1/n)
2017
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hal-01474045v1  Pré-publication, Document de travail
Damien Scieur, Vincent Roulet, Francis Bach, Alexandre D'Aspremont. Integration Methods and Accelerated Optimization Algorithms
2017
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hal-01478317v1  Pré-publication, Document de travail
Kevin Scaman, Francis Bach, Sébastien Bubeck, Yin Tat Lee, Laurent Massoulié. Optimal algorithms for smooth and strongly convex distributed optimization in networks
2017
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inria-00512556v1  Rapport
Julien Mairal, Rodolphe Jenatton, Guillaume Obozinski, Francis Bach. Network Flow Algorithms for Structured Sparsity
[Research Report] RR-7372, INRIA. 2010, pp.23
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hal-00413473v1  Pré-publication, Document de travail
Francis Bach. High-Dimensional Non-Linear Variable Selection through Hierarchical Kernel Learning
2009
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hal-00757696v4  Article dans une revue
Francis Bach. Duality between subgradient and conditional gradient methods
SIAM Journal of Optimization, 2015, 25 (1), pp.115-129. <10.1137/130941961>
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hal-00860051v2  Pré-publication, Document de travail
Mark Schmidt, Nicolas Le Roux, Francis Bach. Minimizing Finite Sums with the Stochastic Average Gradient
Revision from January 2015 submission. Major changes: updated literature follow and discussion of.. 2016
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hal-00860575v1  Pré-publication, Document de travail
K. S. Sesh Kumar, Francis Bach. Maximizing submodular functions using probabilistic graphical models
2013
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hal-00861118v1  Pré-publication, Document de travail
Francis Bach. Convex relaxations of structured matrix factorizations
2013
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hal-00511310v3  Communication dans un congrès
Francis Bach. Structured sparsity-inducing norms through submodular functions
NIPS 2010 : Twenty-Fourth Annual Conference on Neural Information Processing Systems, 2010, Vancouver, Canada. pp.NIPS, 2010
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hal-00527714v2  Pré-publication, Document de travail
Francis Bach. Convex Analysis and Optimization with Submodular Functions: a Tutorial
2010
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hal-00645271v2  Ouvrage (y compris édition critique et traduction)
Francis Bach. Learning with Submodular Functions: A Convex Optimization Perspective
Now Publishers, pp.228, 2013, Foundations and Trends in Machine Learning, 978-1-60198-756-3. <10.1561/2200000039>
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hal-01321532v1  Communication dans un congrès
Francis Bach, Vianney Perchet. Highly-Smooth Zero-th Order Online Optimization Vianney Perchet
Conference on Learning Theory (COLT), Jun 2016, New York, United States. 2016
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inria-00618152v3  Communication dans un congrès
Mark Schmidt, Nicolas Le Roux, Francis Bach. Convergence Rates of Inexact Proximal-Gradient Methods for Convex Optimization
NIPS'11 - 25 th Annual Conference on Neural Information Processing Systems, Dec 2011, Grenada, Spain. 2011
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hal-00674995v4  Communication dans un congrès
Nicolas Le Roux, Mark Schmidt, Francis Bach. A Stochastic Gradient Method with an Exponential Convergence Rate for Finite Training Sets
NIPS'12 - 26 th Annual Conference on Neural Information Processing Systems (2012), 2012, Lake Tahoe, United States. 2012
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hal-01161759v3  Pré-publication, Document de travail
K. S. Sesh Kumar, Francis Bach. Active-set Methods for Submodular Minimization Problems
2016
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hal-00271289v2  Pré-publication, Document de travail
Francis Bach. Bolasso: model consistent Lasso estimation through the bootstrap
2008
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hal-00831977v1  Communication dans un congrès
Francis Bach, Eric Moulines. Non-strongly-convex smooth stochastic approximation with convergence rate O(1/n)
Neural Information Processing Systems (NIPS), Dec 2013, United States. 2013
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hal-00681128v2  Communication dans un congrès
Francis Bach, Simon Lacoste-Julien, Guillaume Obozinski. On the Equivalence between Herding and Conditional Gradient Algorithms
ICML 2012 International Conference on Machine Learning, Jun 2012, Edimburgh, United Kingdom. 2012
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hal-00608041v1  Communication dans un congrès
Francis Bach, Eric Moulines. Non-Asymptotic Analysis of Stochastic Approximation Algorithms for Machine Learning
Neural Information Processing Systems (NIPS), 2011, Spain. 2011
hal-00907528v1  Communication dans un congrès
Fajwel Fogel, Rodolphe Jenatton, Francis Bach, Alexandre D'Aspremont. Convex Relaxations for Permutation Problems
Neural Information Processing Systems (NIPS) 2013, Dec 2013, United States. http://nips.cc/Conferences/2013/Program/speaker-info.php?ID=12863, 2013
hal-00907531v1  Article dans une revue
Alexandre D'Aspremont, Francis Bach, Laurent El Ghaoui. Approximation Bounds for Sparse Principal Component Analysis
Mathematical Programming B, Springer, 2014, 148 (1-2), pp.89-110
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