Timezone: »
Poster
A Multiplicative Weights Algorithm for Apprenticeship Learning
Umar Syed · Robert E Schapire
Author Information
Umar Syed (University of Pennsylvania)
Robert E Schapire (MIcrosoft Research)
Robert Schapire received his ScB in math and computer science from Brown University in 1986, and his SM (1988) and PhD (1991) from MIT under the supervision of Ronald Rivest. After a short post-doc at Harvard, he joined the technical staff at AT&T Labs (formerly AT&T Bell Laboratories) in 1991 where he remained for eleven years. At the end of 2002, he became a Professor of Computer Science at Princeton University. His awards include the 1991 ACM Doctoral Dissertation Award, the 2003 Gödel Prize and the 2004 Kanelakkis Theory and Practice Award (both of the last two with Yoav Freund). His main research interest is in theoretical and applied machine learning.
Related Events (a corresponding poster, oral, or spotlight)
-
2007 Oral: A Multiplicative Weights Algorithm for Apprenticeship Learning »
Wed. Dec 5th 12:40 -- 01:00 AM Room
More from the Same Authors
-
2014 Poster: A Drifting-Games Analysis for Online Learning and Applications to Boosting »
Haipeng Luo · Robert E Schapire -
2010 Poster: A Reduction from Apprenticeship Learning to Classification »
Umar Syed · Robert E Schapire -
2010 Oral: Semi-Supervised Learning with Adversarially Missing Label Information »
Umar Syed · Ben Taskar -
2010 Oral: A Theory of Multiclass Boosting »
Indraneel Mukherjee · Robert E Schapire -
2010 Poster: Semi-Supervised Learning with Adversarially Missing Label Information »
Umar Syed · Ben Taskar -
2010 Poster: A Theory of Multiclass Boosting »
Indraneel Mukherjee · Robert E Schapire -
2010 Poster: Non-Stochastic Bandit Slate Problems »
Satyen Kale · Lev Reyzin · Robert E Schapire -
2009 Poster: Adapting to the Shifting Intent of Search Queries »
Umar Syed · Aleksandrs Slivkins · Nina Mishra -
2007 Oral: FilterBoost: Regression and Classification on Large Datasets »
Joseph K Bradley · Robert E Schapire -
2007 Poster: FilterBoost: Regression and Classification on Large Datasets »
Joseph K Bradley · Robert E Schapire -
2007 Tutorial: Theory and Applications of Boosting »
Robert E Schapire