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» Markov Approximation for Combinatorial Network Optimization
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UAI
1997
14 years 11 months ago
A Scheme for Approximating Probabilistic Inference
This paper describes a class ofprobabilistic approximation algorithms based on bucket elimination which o er adjustable levels of accuracy ande ciency. We analyzethe approximation...
Rina Dechter, Irina Rish
DATAMINE
2010
175views more  DATAMINE 2010»
14 years 9 months ago
Extracting influential nodes on a social network for information diffusion
We address the combinatorial optimization problem of finding the most influential nodes on a large-scale social network for two widely-used fundamental stochastic diffusion models...
Masahiro Kimura, Kazumi Saito, Ryohei Nakano, Hiro...
INFOCOM
2009
IEEE
15 years 4 months ago
Network Bandwidth Allocation via Distributed Auctions with Time Reservations
—This paper studies the problem of allocating network capacity through periodic auctions. Motivated primarily by a service overlay architecture, we impose the following condition...
Pablo Belzarena, Andrés Ferragut, Fernando ...
TSP
2008
101views more  TSP 2008»
14 years 9 months ago
Optimal Node Density for Detection in Energy-Constrained Random Networks
The problem of optimal node density maximizing the Neyman-Pearson detection error exponent subject to a constraint on average (per node) energy consumption is analyzed. The spatial...
Animashree Anandkumar, Lang Tong, Ananthram Swami
NCA
2008
IEEE
14 years 9 months ago
Neurodynamic programming: a case study of the traveling salesman problem
The paper focuses on the study of solving the large-scale traveling salesman problem (TSP) based on neurodynamic programming. From this perspective, two methods, temporal differenc...
Jia Ma, Tao Yang, Zeng-Guang Hou, Min Tan, Derong ...