We propose and analyze a distribution learning algorithm for variable memory length Markov processes. These processes can be described by a subclass of probabilistic nite automata...
Background: Features of a DNA sequence can be found by compressing the sequence under a suitable model; good compression implies low information content. Good DNA compression mode...
Trevor I. Dix, David R. Powell, Lloyd Allison, Jul...
Linux is the most popular open source project. The Linux random number generator is part of the kernel of all Linux distributions and is based on generating randomness from entrop...
We propose and analyze a distribution learning algorithm for a subclass of Acyclic Probabilistic Finite Automata (APFA). This subclass is characterized by a certain distinguishabi...
Abstract. We provide a framework for distributed systems that impose timing constraints on their executions. We propose a timed model of communicating finite-state machines, which...