article · 2008

Algorithm

Anand Rangarajan, Alan Yuille, Eric Mjolsness

Cited by 0Abstract and details only

Abstract

The softassign quadratic assignment algoithm is a discrete time, continuous state, synchronous updating optimizing neural network. While its effectiveness has been shown in the traveling salesman problem, graph matching and graph partitioning in thousands of simulations, there was no associated study of its convergence properties. Here, we construct discrete time Lyapunov functions for the cases of exact and approximate doubly stochastic constraint satisfaction which can be used to show convergence to a fixed point. The combination of good convergence properties and experimental success make the softassign algorithm the technique of choice for neural QAP optimization. 1

Cite this paper

APA 7

Rangarajan, A., Yuille, A., & Mjolsness, E. (2008). Algorithm.

MLA 9

Rangarajan, Anand, et al. “Algorithm.” 2008.

Chicago

Rangarajan, Anand, Alan Yuille, and Eric Mjolsness. 2008. “Algorithm.”

Harvard

Rangarajan, A., Yuille, A. and Mjolsness, E. (2008) ‘Algorithm’.

BibTeX

@article{rangarajan2008algorithm,
  title = {{Algorithm}},
  author = {Rangarajan, Anand and Yuille, Alan and Mjolsness, Eric},
  year = {2008}
}

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