Similar Papers

Paper Title
Journal
Date
Author
Accelerated Non-negative Latent Factor Analysis on High-Dimensional and Sparse Matrices via Generalized Momentum Method
Zhigang Liu ... Xin Luo
-
Zhigang Liu, et. al.Zhigang Liu ... Xin Luo
01 Oct 2018
Unconstrained Non-negative Factorization of High-dimensional and Sparse Matrices in Recommender Systems
Xin Luo ... Mengchu Zhou
-
Xin Luo, et. al.Xin Luo ... Mengchu Zhou
01 Aug 2018
Fast and Accurate Non-Negative Latent Factor Analysis of High-Dimensional and Sparse Matrices in Recommender Systems
Xin Luo ... Zhigang Liu
IEEE Transactions on Knowledge and Data Engineering | VOL. 35
Xin Luo, et. al.Xin Luo ... Zhigang Liu
01 Apr 2023
An Adam-adjusting-antennae BAS Algorithm for Refining Latent Factor Analysis Model
Yuanyi Liu ... Di Wu
-
Yuanyi Liu, et. al.Yuanyi Liu ... Di Wu
09 Oct 2022
View more papers

More From: IEEE Transactions on Emerging Topics in Computational Intelligence

Paper Title
Journal
Date
Author
A Deep Reinforcement Learning-Based Adaptive Large Neighborhood Search for Capacitated Electric Vehicle Routing Problems
Chao Wang ... Xingyi Zhang
IEEE Transactions on Emerging Topics in Computational Intelligence | VOL. 9
Chao Wang, et. al.Chao Wang ... Xingyi Zhang
01 Feb 2025
IEEE Transactions on Emerging Topics in Computational Intelligence Publication Information
-
IEEE Transactions on Emerging Topics in Computational Intelligence | VOL. -
--
01 Feb 2025
Early Time Series Anomaly Prediction With Multi-Objective Optimization
Ting-En Chao ... Vincent S Tseng
IEEE Transactions on Emerging Topics in Computational Intelligence | VOL. 9
Ting-En Chao, et. al.Ting-En Chao ... Vincent S Tseng
01 Feb 2025
IEEE Transactions on Emerging Topics in Computational Intelligence Information for Authors
-
IEEE Transactions on Emerging Topics in Computational Intelligence | VOL. -
--
01 Feb 2025
View more papers

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.