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Sparse methods for machine learning: Theory and algorithms NIPS 2009 Tutorial Francis Bach (INRIA - Ecole Normale Supérieure, Paris) Slides (6.5 Mb) Slides (low-resolution images - 1.9 Mb) Abstract Regularization by the L1-norm has attracted a lot of interest in recent years in statistics, machine learning and signal processing. In the context of least-square linear regression, the problem is usua
Bertille Follain, co-advised with Umut Simsekli Marc Lambert, co-advised with Silvère Bonnabel Ivan Lerner, co-advised with Anita Burgun et Antoine Neuraz Simon Martin, co-advised with Giulio Biroli Céline Moucer, co-advised with Adrien Taylor Anant Raj, co-advised with Maxim Raginsky Corbinian Schlosser, co-advised with Alessandro Rudi Lawrence Stewart, co-advised with Jean-Philippe Vert Alumni M
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