We present multi-task structure learning for Gaussian graphical models. We discuss uniqueness and boundedness of the optimal solution of the maximization problem. A block coordina...
Abstract. We consider batch reinforcement learning problems in continuous space, expected total discounted-reward Markovian Decision Problems. As opposed to previous theoretical wo...
In this paper, we continue our study of learning an optimal kernel in a prescribed convex set of kernels, [18]. We present a reformulation of this problem within a feature space e...
A logistic regression classification algorithm is developed for problems in which the feature vectors may be missing data (features). Single or multiple imputation for the missing...
David Williams, Xuejun Liao, Ya Xue, Lawrence Cari...
This paper extends previous work on the Skewing algorithm, a promising approach that allows greedy decision tree induction algorithms to handle problematic functions such as parit...