JSM Preliminary Online Program
This is the preliminary program for the 2007 Joint Statistical Meetings in Salt Lake City, Utah.

The views expressed here are those of the individual authors
and not necessarily those of the ASA or its board, officers, or staff.



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Legend: = Applied Session, = Theme Session, = Presenter
Salt Palace Convention Center = “CC”, Grand America = “GA”

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446 Applied Session Theme Session Wed, 8/1/07, 2:00 PM - 3:50 PM CC-155 E
Recent Advances in Statistical Learning: Modern Regularization Methods and Semi-supervised Learning - Invited - Papers
Section on Statistical Computing, Section on Nonparametric Statistics
Organizer(s): Hui Zou, The University of Minnesota
Chair(s): Jinchi Lv, Princeton University
     2:05 PM   Efficient Large-Margin Semisupervised Learning — Junhui Wang, Columbia University; Xiaotong Shen, The University of Minnesota
     2:35 PM   Infinite Dimensional LassoNathan Srebro, Toyota Technological Institute at Chicago; Saharon Rosset, IBM T.J. Watson Research Center; Ji Zhu, University of Michigan; Grzegorz Swirszcz, IBM T.J. Watson Research Center
     3:05 PM   Grouped and Hierarchical Model Selection through Composite Absolute Penalties — Peng Zhao, University of California, Berkeley; Guilherme V. Rocha, University of California, Berkeley; Bin Yu, University of California, Berkeley
     3:35 PM   Floor Discussion
 

JSM 2007 For information, contact jsm@amstat.org or phone (888) 231-3473. If you have questions about the Continuing Education program, please contact the Education Department.
Revised September, 2007