Background: Covariance models (CMs) are probabilistic models of RNA secondary structure, analogous to profile hidden Markov models of linear sequence. The dynamic programming algo...
Abstract. In this paper we analyze the complexity of checking safety and termination properties, for a very simple, yet non-trivial, class of programs with singly-linked list data ...
Stochastic programming problems appear as mathematical models for optimization problems under stochastic uncertainty. Most computational approaches for solving such models are base...
We present the first PAC bounds for learning parameters of Conditional Random Fields [12] with general structures over discrete and real-valued variables. Our bounds apply to com...
The fact that graphics processors (GPUs) are today’s most powerful computational hardware for the dollar has motivated researchers to utilize the ubiquitous and powerful GPUs fo...