This paper describes a novel application of Statistical Learning Theory (SLT) for motion prediction. SLT provides analytical VC-generalization bounds for model selection; these bo...
Harry Wechsler, Zoran Duric, Fayin Li, Vladimir Ch...
We introduce the posterior probabilistic clustering (PPC), which provides a rigorous posterior probability interpretation for Nonnegative Matrix Factorization (NMF) and removes th...
We consider the problem of learning sparse parities in the presence of noise. For learning parities on r out of n variables, we give an algorithm that runs in time poly log 1 δ , ...
Abstract. The application of reinforcement learning algorithms to multiagent domains may cause complex non-convergent dynamics. The replicator dynamics, commonly used in evolutiona...
Alessandro Lazaric, Jose Enrique Munoz de Cote, Fa...
In this paper, an educational software aimed to help learning Information Theory basics in a practical way is reported. The software, called IT-tutor-UV, can produce entropy analy...