Presynthesis optimizations transform a behavioral HDL description into an optimized HDL description that results in improved synthesis results. In this paper we introduce the decom...
Abstract. This paper presents a formulation of an optimality principle for a new class of concurrent decision systems formed by products of deterministic Markov decision processes ...
The majority of the existing algorithms for learning decision trees are greedy--a tree is induced top-down, making locally optimal decisions at each node. In most cases, however, ...
We give an optimal dynamic programming algorithm to solve a class of finite-horizon decentralized Markov decision processes (MDPs). We consider problems with a broadcast informati...
Abstract. We give a (ln n + 1)-approximation for the decision tree (DT) problem. An instance of DT is a set of m binary tests T = (T1, . . . , Tm) and a set of n items X = (X1, . ....