Learning Bayesian networks from data is an N-P hard problem with important practical applications. Several researchers have designed algorithms to overcome the computational comple...
In this paper, a generic optimization problem arising in supply chain design is modeled in a game theoretic framework and solved as a decentralized problem using a mechanism desig...
We use techniques from sample-complexity in machine learning to reduce problems of incentive-compatible mechanism design to standard algorithmic questions, for a wide variety of r...
Maria-Florina Balcan, Avrim Blum, Jason D. Hartlin...
— In this paper, we illustrate the use of a reference point based many-objective particle swarm optimization algorithm to optimize low-speed airfoil aerodynamic designs. Our fram...
Upali K. Wickramasinghe, Robert Carrese, Xiaodong ...
In Combinatorial Public Projects, there is a set of projects that may be undertaken, and a set of selfinterested players with a stake in the set of projects chosen. A public plann...