Reinforcement learning deals with learning optimal or near optimal policies while interacting with the environment. Application domains with many continuous variables are difficul...
In many reinforcement learning applications, the set of possible actions can be partitioned by the programmer into subsets of similar actions. This paper presents a technique for ...
Abstract: We investigate the structure of model selection problems via the bias/variance decomposition. In particular, we characterize the essential structure of a model selection ...
Abstract. Sequence to structure alignment is an important step in homology modeling of protein structures. Incorporation of features like secondary structure, solvent accessibility...
Chun-Nam John Yu, Thorsten Joachims, Ron Elber, Ja...
Abstract. Classifying finite algebraic structures has been a major motivation behind much research in pure mathematics. Automated techniques have aided in this process, but this ha...
Simon Colton, Andreas Meier, Volker Sorge, Roy L. ...