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» Approximation Algorithms for Dominating Set in Disk Graphs
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TPDS
2008
136views more  TPDS 2008»
14 years 9 months ago
Data Gathering with Tunable Compression in Sensor Networks
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...
SMI
2008
IEEE
107views Image Analysis» more  SMI 2008»
15 years 4 months ago
Approximate topological matching of quadrilateral meshes
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...
STOC
2004
ACM
88views Algorithms» more  STOC 2004»
15 years 10 months ago
Expander flows, geometric embeddings and graph partitioning
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...
Sanjeev Arora, Satish Rao, Umesh V. Vazirani
CORR
2010
Springer
166views Education» more  CORR 2010»
14 years 9 months ago
The dynamics of message passing on dense graphs, with applications to compressed sensing
`Approximate message passing' algorithms proved to be extremely effective in reconstructing sparse signals from a small number of incoherent linear measurements. Extensive num...
Mohsen Bayati, Andrea Montanari
ILP
2003
Springer
15 years 2 months ago
Graph Kernels and Gaussian Processes for Relational Reinforcement Learning
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 ...
Thomas Gärtner, Kurt Driessens, Jan Ramon