Factored representations, model-based learning, and hierarchies are well-studied techniques for improving the learning efficiency of reinforcement-learning algorithms in large-sca...
Carlos Diuk, Alexander L. Strehl, Michael L. Littm...
In this paper, we propose a set of novel regression-based approaches to effectively and efficiently summarize frequent itemset patterns. Specifically, we show that the problem of ...
This work focuses on the basic stochastic decomposition (SD) algorithm of Higle and Sen [J.L. Higle, S. Sen, Stochastic Decomposition, Kluwer Academic Publishers, 1996] for two-st...
Recently it was observed, that a combined formulation of tracking and reconstruction increases the robustness and accuracy of both these steps in structure-from-motion problems [9...
Clustering and scheduling of tasks for parallel implementation is a well researched problem. Several techniques have been presented in the literature to improve performance and re...