mlsanityData to 14 Oct 2026

Improved Algorithm for the Network Alignment Problem with Application to Binary Diffing

arXiv 2112.15336 ↗First posted 31 Dec 2021cs.LG cs.DC stat.MLcited by 0

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Abstract (arXiv)

In this paper, we present a novel algorithm to address the Network Alignment problem. It is inspired from a previous message passing framework of Bayati et al. [2] and includes several modifications designed to significantly speed up the message updates as well as to enforce their convergence. Experiments show that our proposed model outperforms other state-of-the-art solvers. Finally, we propose an application of our method in order to address the Binary Diffing problem. We show that our solution provides better assignment than the reference differs in almost all submitted instances and outline the importance of leveraging the graphical structure of binary programs.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 5 of its 31 references that are in the map. First posted on arXiv 31 Dec 2021.

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References · 5

  1. 2013Loopy Belief Propagation for Approximate Inference: An Empirical Studycited by 76
  2. 2014Graph Matching: Relax at Your Own Riskcited by 27
  3. 2019KerGM: Kernelized Graph Matchingcited by 13
  4. 2016Spectral Alignment of Graphscited by 12
  5. 2020Rigid and Articulated Point Registration with Expectation Conditional Maximizationcited by 11

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