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AAAI
2007
15 years 9 months ago
Learning Voting Trees
Binary voting trees provide a succinct representation for a large and prominent class of voting rules. In this paper, we investigate the PAC-learnability of this class of rules. W...
Ariel D. Procaccia, Aviv Zohar, Yoni Peleg, Jeffre...
AAAI
2008
15 years 9 months ago
Potential-based Shaping in Model-based Reinforcement Learning
Potential-based shaping was designed as a way of introducing background knowledge into model-free reinforcement-learning algorithms. By identifying states that are likely to have ...
John Asmuth, Michael L. Littman, Robert Zinkov
ACSC
2005
IEEE
15 years 8 months ago
Gradiance On-Line Accelerated Learning
Gradiance On-Line Accelerated Learning GOAL is a system for creating and automatically grading homeworks, programming laboratories, and tests. Through the concept of root questi...
Jeffrey D. Ullman
PR
2006
93views more  PR 2006»
15 years 6 months ago
Learning the kernel parameters in kernel minimum distance classifier
Choosing appropriate values for kernel parameters is one of the key problems in many kernel-based methods because the values of these parameters have significant impact on the per...
Daoqiang Zhang, Songcan Chen, Zhi-Hua Zhou
ICCV
2007
IEEE
16 years 8 months ago
Boosting Invariance and Efficiency in Supervised Learning
In this paper we present a novel boosting algorithm for supervised learning that incorporates invariance to data transformations and has high generalization capabilities. While on...
Andrea Vedaldi, Paolo Favaro, Enrico Grisan