Robust factorization machine: A doubly capped norms minimization

• Main Authors: LIU, Chenghao, ZHANG, Teng, LI, Jundong, YIN, Jianwen, ZHAO, Peilin, SUN, Jianling, HOI, Steven C. H.
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2019
• Subjects: Factorization machines; Feature engineerings; Feature interactions; Loss minimization; Modeling process; Rank minimizations; Real-world datasets; State of the art; Artificial Intelligence and Robotics; Databases and Information Systems; Software Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/4389; https://ink.library.smu.edu.sg/context/sis_research/article/5392/viewcontent/SDM19_RFM.pdf
• Institution: Singapore Management University

Factorization Machine (FM) is a general supervised learning framework for many AI applications due to its powerful capability of feature engineering. Despite being extensively studied, existing FM methods have several limitations in common. First of all, most existing FM methods often adopt the squa...