We consider the problem of multi-task reinforcement learning, where the agent needs to solve a sequence of Markov Decision Processes (MDPs) chosen randomly from a fixed but unknow...
Aaron Wilson, Alan Fern, Soumya Ray, Prasad Tadepa...
Mutual information (MI) based image-registration methods that use histograms are known to suffer from the so-called binning problem, caused by the absence of a principled techniqu...
Multinomial distributions over words are frequently used to model topics in text collections. A common, major challenge in applying all such topic models to any text mining proble...
The improved T and improved n models are proposed for onchip interconnect macromodeling. Using global approximations, simple approximation frames are derived and applied to modeli...
We propose a simple distributed algorithm for balancing indivisible tokens on graphs. The algorithm is completely deterministic, though it tries to imitate (and enhance) a random ...
Tobias Friedrich, Martin Gairing, Thomas Sauerwald