This paper presents a novel evolutionary approach of approximating the shape of the Pareto-optimal set of multi-objective optimization problems. The evolutionary algorithm (EA) use...
We consider the average cost problem for partially observable Markov decision processes (POMDP) with finite state, observation, and control spaces. We prove that there exists an -...
—This paper derives the optimal search time and the optimal search cost that can be achieved in unstructured peer-topeer networks when the demand pattern exhibits clustering (i.e...
We study the design and approximation of optimal crowdsourcing contests. Crowdsourcing contests can be modeled as all-pay auctions because entrants must exert effort up-front to e...
Shuchi Chawla, Jason D. Hartline, Balasubramanian ...
We introduce XPORT, a profile-driven distributed data dissemination system that supports an extensible set of data types, profile types, and optimization metrics. XPORT efficientl...