This paper deals with value (and Q-) function approximation in deterministic Markovian decision processes (MDPs). A general statistical framework based on the Kalman filtering pa...
Abstract. We study online learning algorithms that predict by combining the predictions of several subordinate prediction algorithms, sometimes called “experts.” These simple a...
Yoav Freund, Robert E. Schapire, Yoram Singer, Man...
An important problem in biological data analysis is to predict the family of a newly discovered sequence like a protein or DNA sequence, using the collection of available sequence...
This paper investigates how to represent and solve multiagent task scheduling as a Distributed Constraint Optimization Problem (DCOP). Recently multiagent researchers have adopted...
Evan Sultanik, Pragnesh Jay Modi, William C. Regli
The choice of the kernel function is crucial to most applications of support vector machines. In this paper, however, we show that in the case of text classification, term-frequenc...