Ensemble methods like bagging and boosting that combine the decisions of multiple hypotheses are some of the strongest existing machine learning methods. The diversity of the memb...
Abstract. Many reinforcement learning domains are highly relational. While traditional temporal-difference methods can be applied to these domains, they are limited in their capaci...
Trevor Walker, Lisa Torrey, Jude W. Shavlik, Richa...
This paper introduces a novel method for obtaining increased predictive performance from transparent models in situations where production input vectors are available when building...
In this paper we discuss a data mining framework for constructing intrusion detection models. The key ideas are to mine system audit data for consistent and useful patterns of pro...
In this paper, a hybrid learning approach named HDT is proposed. HDT simulates human reasoning by using symbolic learning to do qualitative analysis and using neural learning to d...