Francis R. Bach
homepage:http://www.di.ens.fr/~fbach/
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Description

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.


Lectures:

tutorial
flag Sparse Methods for Machine Learning: Theory and Algorithms
as author at  23rd Annual Conference on Neural Information Processing Systems (NIPS), Vancouver 2009,
36741 views
  lecture
flag Machine learning and kernel methods for computer vision
as author at  Emerging Trends in Visual Computing,
17451 views
invited talk
flag 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
  invited talk
flag 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,
7118 views
invited talk
flag Learning with Submodular Functions: A Convex Optimization Perspective
as author at  Discrete Optimization in Machine Learning,
7574 views
  lecture
flag Multiple kernel learning for multiple sources
as author at  NIPS Workshop on Learning from Multiple Sources, Whistler 2008,
9322 views
lecture
flag Welcome address
as chairman at  32nd International Conference on Machine Learning (ICML), Lille 2015,
together with: David Blei (chairman), Joelle Pineau (chairman),
3279 views
  lecture
flag Bolasso: Model Consistent Lasso Estimation through the Bootstrap
as author at  25th International Conference on Machine Learning (ICML), Helsinki 2008,
5921 views
lecture
flag Structured sparsity-inducing norms through submodular functions
as author at  Oral Sessions,
5000 views
  lecture
flag Sharp analysis of low-rank kernel matrix approximations
as author at  26th Annual Conference on Learning Theory (COLT), Princeton 2013,
3915 views
invited talk
flag Sharp analysis of low-rank kernel matrix approximations
as author at  Optimization for Machine Learning,
4008 views
  lecture
flag Temporal Segmentation with Kernel Change-point Detection
as author at  Temporal Segmentation,
4801 views
demonstration video
flag Non-Asymptotic Analysis of Stochastic Approximation Algorithms for Machine Learning
as author at  Video Journal of Machine Learning Abstracts - Volume 2,
3843 views
  lecture
flag Convex Sparse Methods for Feature Hierarchies
as author at  Workshops,
4451 views
lecture
flag Second Order Optimization of Kernel Parameters
as presenter at  NIPS Workshop on Kernel Learning: Automatic Selection of Optimal Kernels, Whistler 2008,
4593 views
  lecture
flag 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
lecture
flag Graph Kernels Between Point Clouds
as author at  25th International Conference on Machine Learning (ICML), Helsinki 2008,
4568 views
  poster
flag Non-strongly-convex smooth stochastic approximation with convergence rate O(1/n)
as author at  Video Journal of Machine Learning Abstracts - Volume 5,
1987 views