We study the worst-case communication complexity of distributed algorithms computing a path problem based on stationary distributions of random walks in a network G with the caveat...
This paper presents multi-conditional learning (MCL), a training criterion based on a product of multiple conditional likelihoods. When combining the traditional conditional proba...
Andrew McCallum, Chris Pal, Gregory Druck, Xuerui ...
Abstract. Context-aware systems must be able to deal with uncertain context information. We propose a generic context architecture and representation that incorporates the uncertai...
A major challenge in developing models for hypertext retrieval is to effectively combine content information with the link structure available in hypertext collections. Although s...
This paper describes several ensemble methods that combine multiple different reinforcement learning (RL) algorithms in a single agent. The aim is to enhance learning speed and fin...