We describe an algorithm for learning in the presence of multiple criteria. Our technique generalizes previous approaches in that it can learn optimal policies for all linear pref...
We show a close relationship between the Expectation - Maximization (EM) algorithm and direct optimization algorithms such as gradientbased methods for parameter learning. We iden...
Ruslan Salakhutdinov, Sam T. Roweis, Zoubin Ghahra...
We present the first efficient approach to global routing that takes spacing-dependent costs into account and provably finds a near-optimum solution including these costs. We sh...
Abstract. We present a modified version of the Particle swarm Optimization algorithm in which we adjust the virtual swarm search by incorporating inter-agent dynamics native to mul...
Some of the most successful algorithms for satisfiability, such as Walksat, are based on random walks. Similarly, local search algorithms for solving constraint optimization proble...