Belief Propagation and Algorithms for Mean-Field Combinatorial Optimisations

Belief Propagation and Algorithms for Mean-Field Combinatorial Optimisations

We study combinatorial optimization problems on graphs in the mean-field model, which assigns independent and identically distributed random weights to the edges of the graph. Specifically, we focus on two generalizations of minimum weight matching on graphs. The first problem of minimum cost edge co...

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Bibliographic Details
Main Author: Khandwawala, Mustafa
Other Authors: Sundareasan, Rajesh
Language:en_US
Published: 2017
Subjects:
Combinatorial Optimization
Belief Propagation Algorithms
Local Weak Convergence
Recursive Distributional Equations (RDEs)
Edge-Cover
Many-to-one Matchings
Combinatorial Probability
Mean Field Combinatorial Optimizations
Mean-Field Model
Computer Science
Online Access:http://hdl.handle.net/2005/2764
http://etd.ncsi.iisc.ernet.in/abstracts/3628/G26020-Abs.pdf

Internet

http://hdl.handle.net/2005/2764
http://etd.ncsi.iisc.ernet.in/abstracts/3628/G26020-Abs.pdf

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