We address the problem of the combination of multiple data partitions, that we call a clustering ensemble. We use a recent clustering approach, known as Spectral Clustering, and th...
We consider the problem of scheduling unit-length jobs on identical parallel machines such that the makespan of the resulting schedule is minimized. Precedence constraints impose ...
Daniel W. Engels, Jon Feldman, David R. Karger, Ma...
We present a technique that provides progressive transmission and near-lossless compression in one single framework. The proposed technique produces a bitstream that results in pr...
The inference of evolutionary trees using approaches which attempt to solve the maximum parsimony (MP) and maximum likelihood (ML) optimization problems is a standard part of much...
Reinforcement learning (RL) can be impractical for many high dimensional problems because of the computational cost of doing stochastic search in large state spaces. We propose a ...