We present BayesMD, a Bayesian Motif Discovery model with several new features. Three different types of biological a priori knowledge are built into the framework in a modular fa...
Background: Designing appropriate machine learning methods for identifying genes that have a significant discriminating power for disease outcomes has become more and more importa...
This paper proposes a novel error-resilient packet video coding method which is designed to operate on unreliable IP networks suffering from large bursts of packet losses. The mai...
Markov decisionprocesses(MDPs) haveproven to be popular models for decision-theoretic planning, but standard dynamic programming algorithms for solving MDPs rely on explicit, stat...
Abstract. We present an implementation of model-based online reinforcement learning (RL) for continuous domains with deterministic transitions that is specifically designed to achi...