Abstract— This paper presents a parametric model to estimate the DNA-protein binding time using the DNA and protein structures and details of the binding site. To understand the ...
Preetam Ghosh, Samik Ghosh, Kalyan Basu, Sajal K. ...
The method of stochastic state classes approaches the analysis of Generalised Semi Markov Processes (GSMP) through symbolic derivation of probability density functions over Differe...
R-max is a very simple model-based reinforcement learning algorithm which can attain near-optimal average reward in polynomial time. In R-max, the agent always maintains a complet...
Abstract. In this paper we study distributed online learning of locomotion gaits for modular robots. The learning is based on a stochastic approximation method, SPSA, which optimiz...
Stochastic dependency parsers can achieve very good results when they are trained on large corpora that have been manually annotated. Active learning is a procedure that aims at r...