Recently, actor-critic methods have drawn much interests in the area of reinforcement learning, and several algorithms have been studied along the line of the actor-critic strategy...
With the explosion of the size of digital dataset, the limiting factor for decomposition algorithms is the number of passes over the input, as the input is often stored out-of-cor...
Logic-based probabilistic models (LBPMs) enable us to handle problems with uncertainty succinctly thanks to the expressive power of logic. However, most of LBPMs have restrictions...
We present a new algorithm for computing the solution of large Markov chain models whose generators can be represented in the form of a generalized tensor algebra, such as network...