Locally adaptive classifiers are usually superior to the use of a single global classifier. However, there are two major problems in designing locally adaptive classifiers. First,...
Juan Dai, Shuicheng Yan, Xiaoou Tang, James T. Kwo...
In this paper we consider sampling based fitted value iteration for discounted, large (possibly infinite) state space, finite action Markovian Decision Problems where only a gener...
We apply nonparametric hierarchical Bayesian modelling to relational learning. In a hierarchical Bayesian approach, model parameters can be "personalized", i.e., owned b...
Zhao Xu, Volker Tresp, Kai Yu, Shipeng Yu, Hans-Pe...
Bayesian networks are a powerful probabilistic representation, and their use for classification has received considerable attention. However, they tend to perform poorly when lear...
We develop techniques to estimate the statistical significance of gap-free alignments between two genomic DNA sequences, using human-mouse alignments as an example. The sequences ...