We provide tight information-theoretic lower bounds for the welfare maximization problem in combinatorial auctions. In this problem, the goal is to partition m items among k bidde...
Vahab S. Mirrokni, Michael Schapira, Jan Vondr&aac...
-- We encounter optimization problems in our daily lives and in various research domains. Some of them are so hard that we can, at best, approximate the best solutions with (meta-)...
The Relevance Vector Machine (RVM) is a sparse approximate Bayesian kernel method. It provides full predictive distributions for test cases. However, the predictive uncertainties ...
Motivated by a scheduling problem encountered in multicast environments, we study a vertex labelling problem, called Directed Circular Arrangement (DCA), that requires one to fin...
Facility location problems have always been studied with the assumption that the edge lengths in the network are static and do not change over time. The underlyingnetwork could be ...