When text categorization is applied to complex tasks, it is tedious and expensive to hand-label the large amounts of training data necessary for good performance. In this paper, we...
The Bayesian framework of learning from positive noise-free examples derived by Muggleton [12] is extended to learning functional hypotheses from positive examples containing norma...
In large content-based image database applications, e cient information retrieval depends heavily on good indexing structures of the extracted features. While indexing techniques f...
Abstract. We present a new reinforcement learning approach for deterministic continuous control problems in environments with unknown, arbitrary reward functions. The difficulty of...
This paper demonstrates the generality of the hidden Markov model approach for exploratory sequence analysis by applying the methodology to study students' learning behaviors ...