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» Markov Approximation for Combinatorial Network Optimization
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UAI
1997
15 years 28 days 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 11 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 6 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 11 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 11 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 ...