Replication-based inference algorithms for hard computational problems

Roberto C. Alamino*, Juan P. Neirotti, David Saad

*Corresponding author for this work

Research output: Contribution to journalArticle

Abstract

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.

Original languageEnglish
Article number013313
Number of pages10
JournalPhysical Review E
Volume88
Issue number1
DOIs
Publication statusPublished - 31 Jul 2013

Bibliographical note

© 2013 American Physical Society

Fingerprint Dive into the research topics of 'Replication-based inference algorithms for hard computational problems'. Together they form a unique fingerprint.

  • Cite this