Dynamic Bayesian networks are structured representations of stochastic processes. Despite their structure, exact inference in DBNs is generally intractable. One approach to approx...
Reinforcement learning problems are commonly tackled with temporal difference methods, which attempt to estimate the agent's optimal value function. In most real-world proble...
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...
This paper snggests a method to align Korean-English parallel corpus. '1?he structural dissimilarity between Korean and Indo-European languages requires more flexible measure...
This paper deals with the quadratic stability and linear state-feedback and output-feedback stabilization of switched delayed linear dynamic systems with, in general, a finite nu...