Francis Bach is a researcher in the Willow INRIA project-team, in the Computer Science Department of Ecole Normale Supérieure, Paris, France. He graduated from Ecole Polytechnique, Palaiseau, France, in 1997, and earned his PhD in 2005 from the Computer Science division at the University of California, Berkeley. His research interests include machine learning, statistics, convex and combinatorial optimization, graphical models, kernel methods, sparse methods, signal processing and computer vision.
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lecture
Welcome address
as chairman at 32nd International Conference on Machine Learning (ICML), Lille 2015,
together with:
David Blei (chairman),
Joelle Pineau (chairman),
3279 views
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invited talk
Beyond stochastic gradient descent for large-scale machine learning
as author at 1st UCL-Duke University Workshop on Sensing and Analysis of High-Dimensional Data (SAHD), London 2014,
7613 views
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poster
Non-strongly-convex smooth stochastic approximation with convergence rate O(1/n)
as author at Video Journal of Machine Learning Abstracts - Volume 5,
1986 views
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invited talk
Beyond Stochastic Gradient Descent
as author at International Workshop on Advances in Regularization, Optimization, Kernel Methods and Support Vector Machines (ROKS): theory and applications, Leuven 2013,
7117 views
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lecture
Sharp analysis of low-rank kernel matrix approximations
as author at 26th Annual Conference on Learning Theory (COLT), Princeton 2013,
3915 views
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invited talk
Sharp analysis of low-rank kernel matrix approximations
as author at Optimization for Machine Learning,
4008 views
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invited talk
Learning with Submodular Functions: A Convex Optimization Perspective
as author at Discrete Optimization in Machine Learning,
7572 views
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demonstration video
Non-Asymptotic Analysis of Stochastic Approximation Algorithms for Machine Learning
as author at Video Journal of Machine Learning Abstracts - Volume 2,
3843 views
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lecture
Structured sparsity-inducing norms through submodular functions
as author at Oral Sessions,
5000 views
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lecture
Temporal Segmentation with Kernel Change-point Detection
as author at Temporal Segmentation,
4799 views
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tutorial
Sparse Methods for Machine Learning: Theory and Algorithms
as author at 23rd Annual Conference on Neural Information Processing Systems (NIPS), Vancouver 2009,
36737 views
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lecture
Convex Sparse Methods for Feature Hierarchies
as author at Workshops,
4450 views
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lecture
High-Dimensional Non-Linear Variable Selection through Hierarchical Kernel Learning
as author at Workshop on Sparsity in Machine Learning and Statistics, Cumberland Lodge 2009,
4358 views
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lecture
Multiple kernel learning for multiple sources
as author at NIPS Workshop on Learning from Multiple Sources, Whistler 2008,
9322 views
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lecture
Second Order Optimization of Kernel Parameters
as presenter at NIPS Workshop on Kernel Learning: Automatic Selection of Optimal Kernels, Whistler 2008,
4593 views
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lecture
Machine learning and kernel methods for computer vision
as author at Emerging Trends in Visual Computing,
17449 views
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lecture
Bolasso: Model Consistent Lasso Estimation through the Bootstrap
as author at 25th International Conference on Machine Learning (ICML), Helsinki 2008,
5921 views
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lecture
Graph Kernels Between Point Clouds
as author at 25th International Conference on Machine Learning (ICML), Helsinki 2008,
4568 views
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Springer,
