This paper proposes an optimization algorithm for reducing the power dissipation in a sequential circuit. The encoding of the different states in a Finite State Machine is modifie...
S. Chuisano, Fulvio Corno, Paolo Prinetto, Maurizi...
The traditional algorithm of Stockmeyer for area minimization of slicing
oorplans has time (and space) complexity O(n2 ) in the worst case, or O(nlogn) for balanced slicing. For ...
The field of stochastic optimization studies decision making under uncertainty, when only probabilistic information about the future is available. Finding approximate solutions to...
R-max is a very simple model-based reinforcement learning algorithm which can attain near-optimal average reward in polynomial time. In R-max, the agent always maintains a complet...
Abstract— The role of gradient estimation in global optimization is investigated. The concept of a regional gradient is introduced as a tool for analyzing and comparing different...