This monthly seminar aims at presenting and studying various topics in statistical machine learning theory and applications. We mostly present and critically discuss recent publications in this field, organize "hot debriefing" sessions after major international conferences, and occasionally welcome invited speakers from around the world to learn about their latest research.

If you wish to receive the announcements, suggest or be volunteer to present a paper, contact Francis Bach or Jean-Philippe Vert.

Next seminars

• May 14, 2009 : Random features for large scale machine learning

Past seminars

• Apr. 23, 2009 : covariance-regularized regression and sparse PCA
• Feb. 12, 2009 : NIPS compilation 2
• Jan. 22, 2009 : NIPS compilation 1
• Jan. 15, 2009 : Bin Yu (UC Berkeley), Seeking Interpretable Models for High Dimensional Data (at ENSAE ParisTech)
• Dec. 18, 2008 : Laurent El Ghaoui (UC Berkeley), Robustness and regularization: a robust optimization perspective
• Nov. 20, 2008 : L1 penalties to estimate the structure of a graphical model (2)
• Oct. 23, 2008 : L1 penalties to estimate the structure of a graphical model (1)
• Sep. 18, 2008 : ICML compilation
• Jun. 12, 2008 : Csaba Szepesvari (University of Alberta)Active Learning in Multi-Armed Bandits
• May 22, 2008 : The score matching function
• Feb. 21, 2008 : Graphical models, exponential families and variational inference