Decentralized MDPs provide a powerful formal framework for planning in multi-agent systems, but the complexity of the model limits its usefulness. We study in this paper a class o...
Raphen Becker, Shlomo Zilberstein, Victor R. Lesse...
"Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning...
Carl Edward Rasmussen and Christopher K. I. Willia...
Latency has become an important metric for network monitoring since the emergence of new latency-sensitive applications (e.g., algorithmic trading and high-performance computing)....
Myungjin Lee, Nick G. Duffield, Ramana Rao Kompell...
In this paper, we design recommender systems for weblogs based on the link structure among them. We propose algorithms based on refined random walks and spectral methods. First, w...
In this paper we introduce a new method of combined synthesis and inference of biological signal transduction networks. A main idea of our method lies in representing observed cau...