We study the problem of constructing a data gathering tree over a wireless sensor network in order to minimize the total energy for compressing and transporting information from a ...
Yang Yu, Bhaskar Krishnamachari, Viktor K. Prasann...
Abstract In this paper, we study the problem of approximate topological matching for quadrilateral meshes, that is, the problem of finding as large a set as possible of matching p...
David Eppstein, Michael T. Goodrich, Ethan Kim, Ra...
We give a O( log n)-approximation algorithm for sparsest cut, edge expansion, balanced separator, and graph conductance problems. This improves the O(log n)-approximation of Leig...
`Approximate message passing' algorithms proved to be extremely effective in reconstructing sparse signals from a small number of incoherent linear measurements. Extensive num...
RRL is a relational reinforcement learning system based on Q-learning in relational state-action spaces. It aims to enable agents to learn how to act in an environment that has no ...