— Given an arbitrary network of interconnected nodes, each with an initial value from a discrete set, we consider the problem of distributively disseminating these initial values...
The most natural way of thinking about negotiation is probably a situation whereby each of the parties involved initially make a proposal that is particularly beneficial to themse...
Methods for learning Bayesian networks can discover dependency structure between observed variables. Although these methods are useful in many applications, they run into computat...
Eran Segal, Dana Pe'er, Aviv Regev, Daphne Koller,...
Recent work in supervised learning has shown that a surprisingly simple Bayesian classifier with strong assumptions of independence among features, called naive Bayes, is competit...
In this paper, we study a particular subclass of partially observable models, called quasi-deterministic partially observable Markov decision processes (QDET-POMDPs), characterize...