Mechanism design is the study of preference aggregation protocols that work well in the face of self-interested agents. We present the first general-purpose techniques for automa...
Tuomas Sandholm, Vincent Conitzer, Craig Boutilier
We propose a new class of consistency constraints for Linear Programming (LP) relaxations for finding the most probable (MAP) configuration in graphical models. Usual cluster-base...
We consider the problem of multiple kernel learning (MKL), which can be formulated as a convex-concave problem. In the past, two efficient methods, i.e., Semi-Infinite Linear Prog...
Current research in autonomic computing suffers from the lack of a common definition of the basic autonomic entities. Defining and developing the basic autonomic entities and maki...
M. Muztaba Fuad, Debzani Deb, Michael J. Oudshoorn
Markov Decision Processes (MDPs) have been extensively studied and used in the context of planning and decision-making, and many methods exist to find the optimal policy for probl...