Replication-based inference algorithms for hard computational problems

C. Alamino, Roberto, P. Neirotti, Juan and Saad, David Replication-based inference algorithms for hard computational problems. Physical Review E, 88 (1),


Inference algorithms based on evolving interactions between replicated solutions are introduced and analyzed on a prototypical NP-hard problem: the capacity of the binary Ising perceptron. The efficiency of the algorithm is examined numerically against that of the parallel tempering algorithm, showing improved performance in terms of the results obtained, computing requirements and simplicity of implementation. © 2013 American Physical Society.

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Divisions: Engineering & Applied Sciences > Non-linearity and complexity research group
Engineering & Applied Sciences > Mathematics
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Additional Information: © 2013 American Physical Society
Uncontrolled Keywords: Condensed Matter Physics,Statistical and Nonlinear Physics,Statistics and Probability



Version: Published Version

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