A Second-Order Symmetric Non-Negative Latent Factor Model for Undirected Weighted Network Representation

Weiling Li, Renfang Wang, Xin Luo, Meng Chu Zhou

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

Precise representation to undirected weighted network (UWN) is the foundation of understanding connection patterns inside a massive node set. It can be addressed via a Symmetric Non-negative Latent Factor (SNLF) model with a non-convex learning objective. However, existing SNLF models commonly adopt a first-order learning algorithm that cannot well handle such a non-convex objective, thereby leading to inaccurate UWN representation. Aiming at addressing this issue, this study incorporates an efficient second-order learning algorithm into an SNLF model, thereby establishing a Second-order Symmetric Non-negative Latent Factor (S2NLF) model with two-fold ideas: a) applying the single latent factor-related mapping function to the non-negativity constrained optimization parameters to achieve an unconstrained learning objective, and b) optimizing this learning objective with its optimization parameters through an efficient second-order learning algorithm to achieve accurate representation to the target UWN with affordable computational burden. Empirical studies indicate that owing to its efficient incorporation of the second-order optimization technique, the proposed S2NLF model outperforms state-of-the-art SNLF models when they are used to gain highly accurate representation to UWNs emerging from real applications.

Original languageEnglish (US)
Pages (from-to)606-618
Number of pages13
JournalIEEE Transactions on Network Science and Engineering
Volume10
Issue number2
DOIs
StatePublished - Mar 1 2023

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Networks and Communications
  • Computer Science Applications

Keywords

  • Conjugate gradient descent
  • hessian-vector product
  • latent factor analysis
  • representation learning
  • second-order optimization
  • symmetric
  • undirected weighted network

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