Existing algorithms for discrete partially observable Markov decision processes can at best solve problems of a few thousand states due to two important sources of intractability:...
The problem of efficient load distribution and scaling of large-scale wireless communication system simulation on multiprocessor architectures (both shared memory and cluster arra...
Learning from ambiguous training data is highly relevant in many applications. We present a new learning algorithm for classification problems where labels are associated with se...
We study a non-overlapping domain decomposition method for the Oseen-viscoelastic flow problem. The data on the interface are transported through Newmann and Dirichlet boundary co...
This is an introductory survey of the emerging theory of two new classes of (discrete, countable) groups, called hyperlinear and sofic groups. They can be characterized as subgroup...