Active Bibliography

Mathematical Programming manuscript No. (will be inserted by the editor) Pegasos: Primal Estimated sub-GrAdient SOlver for SVM – Shai Shalev-shwartz, Yoram Singer Nathan, Srebro Andrew Cotter, Shai Shalev-shwartz, Yoram Singer, Nathan Srebro, Andrew Cotter
Improved Learning of . . . : TRAINING WITH LATENT VARIABLES AND NONLINEAR KERNELS – Chun Nam Yu - 2011
7 Learning to Search: Structured Prediction Techniques for Imitation Learning – Nathan D. Ratliff, James Kuffner, Andrew Ng - 2009
Computational Trade-offs in Statistical Learning – Alekh Agarwal, Alekh Agarwal, Alekh Agarwal
91 Training a support vector machine in the primal – Olivier Chapelle - 2007
2 Exploiting separability in large-scale linear Support Vector Machine training – Kristian Woodsend, Jacek Gondzio - 2009
Examining Committee: – Frédéric Koriche, Antoine Cornuéjols, Christophe Fiorio, Alain Jean-marie, Jérôme Lang, Pierre Marquis, Abdel-illah Mouaddib, Pascal Poncelet
1 A PAC Bound for Approximate Support Vector Machines – Dongwei Cao, Daniel Boley - 2007
Machine Learning and Data Mining Via Mathematical Programing Based Support Vector Machines By – Glenn Fung - 2003
293 Online passiveaggressive algorithms – Koby Crammer, Ofer Dekel, Shai Shalev-shwartz, Yoram Singer - 2006
35 A Review of Kernel Methods in Machine Learning – Thomas Hofmann, Bernhard Schölkopf, Alexander J. Smola - 2006
373 An introduction to kernel-based learning algorithms – Klaus-Robert Müller, Sebastian Mika, Gunnar Rätsch, Koji Tsuda, Bernhard Schölkopf - 2001
6 Recent Advances of Large-scale Linear Classification – Guo-xun Yuan, Chia-hua Ho, Chih-jen Lin
27 Composite Objective Mirror Descent – John Duchi, Shai Shalev-shwartz, Yoram Singer, Ambuj Tewari
Chapter 13 A User’s Guide to Support Vector Machines – Asa Ben-hur, Jason Weston
Machine Learning manuscript No. (will be inserted by the editor) PAMR: Passive Aggressive Mean Reversion Strategy for Portfolio Selection – Bin Li, Peilin Zhao, Steven C. H. Hoi, Vivekanand Gopalkrishnan, Steven C. H. Hoi, Bin Li, Peilin Zhao, Vivekanand Gopalkrishnan
9 Learning classifiers from distributed, semantically heterogeneous, autonomous data sources – Doina Caragea - 2004
Special Member – Lee Giles, Léon Bottou, Raj Acharya, Jia Li, Tracy Mullen
1 Tree Decomposition for Large-Scale SVM Problems: Experimental and Theoretical Results – Fu Chang, Chien-yang Guo, Xiao-rong Lin, Chi-jen Lu - 2009