Abstract— In this paper, we consider a class of continuoustime, continuous-space stochastic optimal control problems. Building upon recent advances in Markov chain approximation ...
We present a unifying framework for information theoretic feature selection, bringing almost two decades of research on heuristic filter criteria under a single theoretical inter...
Gavin Brown, Adam Pocock, Ming-Jie Zhao, Mikel Luj...
—Conserving network-wide energy consumption is becoming an increasingly important concern for network operators. In this work, we study network-wide energy conservation problem w...
Abstract. Kernel based methods (such as k-nearest neighbors classifiers) for AI tasks translate the classification problem into a proximity search problem, in a space that is usu...
Abstract. The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (th...