W2FM: The Doubly-Warped Factorization Machine

Mao Lin Li, K. Selçuk Candan

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Factorization Machines (FMs) enhance an underlying linear regression or classification model by capturing feature interactions. Intuitively, FMs warp the feature space to help capture the underlying non-linear structure of the machine learning task. In this paper, we propose novel Doubly-Warped Factorization Machines (or W2FM s) that leverage multiple complementary space warping strategies to improve the representational ability of FMs. Our approach abstracts the feature interaction in FMs as additional affine transformations (thus warping the space), which can be learned efficiently without introducing large numbers of model parameters. We also explore alternative W2FM based approaches and conduct extensive experiments on real world data sets. These experiments show that W2FM achieves better performance in collaborative filtering task not only relative to vanilla FMs, but also against other state-of-the-art competitors, such as Attention FM (AFM), Holographic FM (HFM), and Neural FM (NFM).

Original languageEnglish (US)
Title of host publicationAdvances in Knowledge Discovery and Data Mining - 25th Pacific-Asia Conference, PAKDD 2021, Proceedings
EditorsKamal Karlapalem, Hong Cheng, Naren Ramakrishnan, R. K. Agrawal, P. Krishna Reddy, Jaideep Srivastava, Tanmoy Chakraborty
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages13
ISBN (Print)9783030757649
StatePublished - 2021
Event25th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2021 - Virtual, Online
Duration: May 11 2021May 14 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12713 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference25th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2021
CityVirtual, Online


  • Collaborative filtering
  • Factorization machine

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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