This work proposes and evaluates improvements to previously known algorithms for redundancy elimination. Enhanced Scalar Replacement combines two classic techniques, scalar replac...
Current publish / subscribe systems offer a range of expressive subscription languages for constraints. However, classical systems restrict the publish operation to be a single p...
An important investigation of time series involves searching for \movement" patterns, such as \going up" or \going down" or some combinations of them. Movement patt...
Multi-task learning (MTL) aims to improve the performance of multiple related tasks by exploiting the intrinsic relationships among them. Recently, multi-task feature learning alg...
This paper investigates a novel model-free reinforcement learning architecture, the Natural Actor-Critic. The actor updates are based on stochastic policy gradients employing Amari...