We give a general technique to obtain approximation mechanisms that are truthful in expectation. We show that for packing domains, any α-approximation algorithm that also bounds ...
Abstract-- We consider reinforcement learning, and in particular, the Q-learning algorithm in large state and action spaces. In order to cope with the size of the spaces, a functio...
We study the edge-connectivity survivable network design problem with an additional linear budget constraint. We give a strongly polynomial time (3, 3)-approximation algorithm for ...
Abstract. In this paper, we present a new technique for Matsui's algorithm 2 using multidimensional linear approximation. We show that the data complexity of the attack can be...
Abstract. We present a domain theoretic framework for obtaining exact solutions of linear boundary value problems. Based on the domain of compact real intervals, we show how to app...