Abstract— In this paper, we consider a class of continuoustime, continuous-space stochastic optimal control problems. Building upon recent advances in Markov chain approximation ...
Recently, a number of researchers have proposed spectral algorithms for learning models of dynamical systems—for example, Hidden Markov Models (HMMs), Partially Observable Marko...
We consider the problem of derandomizing random walks in the Euclidean space Rk . We show that for k = 2, and in some cases in higher dimensions, such walks can be simulated in Lo...
Phase-type (PH) distributions are proven to be very powerful tools in modelling and analysis of a wide range of phenomena in computer systems. The use of these distributions in sim...
We present improved competitive on-line algorithms for the page replication problem and concentrate on important network topologies for which algorithms with a constant competitiv...