The precise specification of reward functions for Markov decision processes (MDPs) is often extremely difficult, motivating research into both reward elicitation and the robust so...
Planning in partially-observable dynamical systems (such as POMDPs and PSRs) is a computationally challenging task. Popular approximation techniques that have proved successful ar...
Michael R. James, Michael E. Samples, Dmitri A. Do...
Abstract. We consider the single machine scheduling problem to minimize the average weighted completion time under precedence constrains. Improving on the various 2-approximation a...
This paper presents a new approach to extracting and representing structural features of images. The approach is based on both a region-based analysis and a contour-based analysis...
Support Vector Machines (SVMs) suffer from a widely recognized scalability problem in both memory use and computational time. To improve scalability, we have developed a parallel ...
Edward Y. Chang, Kaihua Zhu, Hao Wang, Hongjie Bai...