Recent scaling up of decentralized partially observable Markov decision process (DEC-POMDP) solvers towards realistic applications is mainly due to approximate methods. Of this fa...
Clustering in data mining is a discovery process that groups a set of data such that the intracluster similarity is maximized and the intercluster similarity is minimized. These d...
Eui-Hong Han, George Karypis, Vipin Kumar, Bamshad...
Real-time Garbage Collection (RTGC) has recently advanced to the point where it is being used in production for financial trading, military command-and-control, and telecommunicat...
Joshua S. Auerbach, David F. Bacon, Perry Cheng, D...
We consider the problem of multi-task reinforcement learning, where the agent needs to solve a sequence of Markov Decision Processes (MDPs) chosen randomly from a fixed but unknow...
Aaron Wilson, Alan Fern, Soumya Ray, Prasad Tadepa...
With this work we aim to make a three-fold contribution. We first address the issue of supporting efficiently queries over string-attributes involving prefix, suffix, containmen...