Large-scale text categorization is an important research topic for Web data mining. One of the challenges in large-scale text categorization is how to reduce the amount of human e...
In practical classification, there is often a mix of learnable and unlearnable classes and only a classifier above a minimum performance threshold can be deployed. This problem is...
This paper develops a generalized apprenticeship learning protocol for reinforcementlearning agents with access to a teacher who provides policy traces (transition and reward obse...
Thomas J. Walsh, Kaushik Subramanian, Michael L. L...
R-max is a very simple model-based reinforcement learning algorithm which can attain near-optimal average reward in polynomial time. In R-max, the agent always maintains a complet...
In this paper we generalize the LARS feature selection method to the linear SVM model, derive an efficient algorithm for it, and empirically demonstrate its usefulness as a featur...