Markov decision processes (MDPs) are controllable discrete event systems with stochastic transitions. The payoff received by the controller can be evaluated in different ways, dep...
?Gibbsian fields or Markov random fields are widely used in Bayesian image analysis, but learning Gibbs models is computationally expensive. The computational complexity is pronoun...
We show how a preselection of hidden variables can be used to efficiently train generative models with binary hidden variables. The approach is based on Expectation Maximization (...
Although many researches have investigated transparent scrambling video techniques, an issue of which transcoding relates to downsizing scrambled video without unscrambling has ha...
We consider the problem to sell items to a set of bidders. Bidders bid on bundles of items, and each item's availability is unbounded, like for digital goods. We need to dete...
Alexander Grigoriev, Joyce van Loon, Maxim Sviride...