Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
Recently, a convergence proof of stochastic search algorithms toward finite size Pareto set approximations of continuous multi-objective optimization problems has been given. The...
— This paper addresses model reduction for a Markov chain on a large state space. A simulation-based framework is introduced to perform state aggregation of the Markov chain base...
The spectral profile of a graph is a natural generalization of the classical notion of its Rayleigh quotient. Roughly speaking, given a graph G, for each 0 < < 1, the spect...
Prasad Raghavendra, David Steurer and Prasad Tetal...
We consider the problem of designing a near-optimal linear decision tree to classify two given point sets B and W in n. A linear decision tree de nes a polyhedral subdivision of sp...
Michelangelo Grigni, Vincent Mirelli, Christos H. ...