The paper introduces a new framework for feature learning in classification motivated by information theory. We first systematically study the information structure and present a n...
Abstract. Many large-scale optimization problems rely on graph theoretic solutions; yet high-performance computing has traditionally focused on regular applications with high degre...
Abstract— Standard embeded sensor nework models emphasize energy efficiency and distributed decision-making by considering untethered and unattended sensors. To this we add two ...
Rajgopal Kannan, Sudipta Sarangi, S. Sitharama Iye...
Interactions among agents can be conveniently described by game trees. In order to analyze a game, it is important to derive optimal (or equilibrium) strategies for the di erent p...
Daphne Koller, Nimrod Megiddo, Bernhard von Stenge...
This paper takes an economic approach to derive an evolutionary learning model based entirely on the endogenous employment of genetic operators in the service of self-interested a...