One of the open problems listed in Rivest and Schapire, 1989] is whether and how that the copies of L in their algorithm can be combined into one for better performance. This pape...
Abstract. We adopt the Markov chain framework to model bilateral negotiations among agents in dynamic environments and use Bayesian learning to enable them to learn an optimal stra...
The problem of reinforcement learning in large factored Markov decision processes is explored. The Q-value of a state-action pair is approximated by the free energy of a product o...
We consider a finite-state memoryless channel with i.i.d. channel state and the input Markov process supported on a mixing finite-type constraint. We discuss the asymptotic behavio...
We propose a new parallelization scheme for the hmmsearch function of the HMMER software, in order to target FPGA technology. hmmsearch is a very compute intensive software for bio...