— Modeling robot motion planning with uncertainty in a Bayesian framework leads to a computationally intractable stochastic control problem. We seek hypotheses that can justify a...
Andrea Censi, Daniele Calisi, Alessandro De Luca, ...
We study the combinatorial auction (CA) problem, in which m objects are sold to rational agents and the goal is to maximize social welfare. Of particular interest is the special ca...
We give the first black-box reduction from arbitrary approximation algorithms to truthful approximation mechanisms for a non-trivial class of multiparameter problems. Specifically,...
We show how improved sequences for magnetic resonance imaging can be found through optimization of Bayesian design scores. Combining approximate Bayesian inference and natural ima...
Matthias W. Seeger, Hannes Nickisch, Rolf Pohmann,...
Computational Grids are large scale computing system composed of geographically distributed resources (computers, storage etc.) owned by self interested agents or organizations. T...