There has been little work in explaining recommendations generated by Markov Decision Processes (MDPs). We analyze the difculty of explaining policies computed automatically and id...
The design of inference algorithms for discrete-valued Markov Random Fields constitutes an ongoing research topic in computer vision. Large state-spaces, none-submodular energy-fun...
This paper describes the tool CASPA, a new performance evaluation tool which is based on a Markovian stochastic process algebra. CASPA uses multi-terminal binary decision diagrams ...
We present a dynamic programming approach for the solution of first-order Markov decisions processes. This technique uses an MDP whose dynamics is represented in a variant of the ...
We present a new technique for constructing and analyzing couplings to bound the convergence rate of finite Markov chains. Our main theorem is a generalization of the path couplin...