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...
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 ...
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...
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...
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...