This paper analyzes the complexity of on-line reinforcement learning algorithms, namely asynchronous realtime versions of Q-learning and value-iteration, applied to the problem of...
Abstract. A general parametric analysis problem which allows the use of parameter variables in both the realtime automata and the specifications is proposed and solved. The analys...
We present a new algorithm for Bayesian network structure learning, called Max-Min Hill-Climbing (MMHC). The algorithm combines ideas from local learning, constraint-based, and sea...
Ioannis Tsamardinos, Laura E. Brown, Constantin F....
The problem of rewriting queries using views has received significant attention because of its applications in a wide variety of datamanagement problems. For select-project-join SQ...
Foto N. Afrati, Rada Chirkova, Manolis Gergatsouli...
Background: Eukaryotic promoter prediction using computational analysis techniques is one of the most difficult jobs in computational genomics that is essential for constructing a...