Bargaining networks model the behavior of a set of players who need to reach pairwise agreements for making profits. Nash bargaining solutions in this context correspond to soluti...
Yashodhan Kanoria, Mohsen Bayati, Christian Borgs,...
Multi-instance learning deals with problems that treat bags of instances as training examples. In single-instance learning problems, dimensionality reduction is an essential step ...
Efficient algorithms for collision-free energy sub-optimal path planning for formations of spacecraft flying in deep space are presented. The idea is to introduce a set of way-poi...
A flow of a commodity is said to be confluent if at any node all the flow of the commodity leaves along a single edge. In this paper we study single-commodity confluent flow pro...
Multiobjective optimization in general aims at learning about the problem at hand. Usually the focus lies on objective space properties such as the front shape and the distributio...