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A Multilayered-and-Randomized Latent Factor Model for High-Dimensional and Sparse Matrices 期刊论文
IEEE TRANSACTIONS ON BIG DATA, 2022, 卷号: 8, 期号: 3, 页码: 784-794
作者:  Yuan, Ye;  He, Qiang;  Luo, Xin;  Shang, Mingsheng
收藏  |  浏览/下载：74/0  |  提交时间：2022/08/22
Computational modeling  Sparse matrices  Big Data  Data models  Stochastic processes  Training  Software algorithms  Big data  latent factor analysis  generally multilayered structure  deep forest  multilayered extreme learning machine  randomized-learning  high-dimensional and sparse matrix  stochastic gradient descent  randomized model  
Non-Negative Latent Factor Model Based on beta-Divergence for Recommender Systems 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 卷号: 51, 期号: 8, 页码: 4612-4623
作者:  Xin, Luo;  Yuan, Ye;  Zhou, MengChu;  Liu, Zhigang;  Shang, Mingsheng
收藏  |  浏览/下载：129/0  |  提交时间：2021/08/20
beta-divergence  big data  high-dimensional and sparse (HiDS) matrix  industrial application  learning algorithm  non-negative latent factor (NLF) analysis  recommender system  
A proportional-integral-derivative-incorporated stochastic gradient descent-based latent factor analysis model 期刊论文
NEUROCOMPUTING, 2021, 卷号: 427, 页码: 29-39
作者:  Li, Jinli;  Yuan, Ye;  Ruan, Tao;  Chen, Jia;  Luo, Xin
收藏  |  浏览/下载：94/0  |  提交时间：2021/03/17
Big data  Stochastic gradient descent  Proportional integral derivation  PID controller  High-dimensional and sparse matrix  Latent factor analysis  
An alpha -beta -Divergence-Generalized Recommender for Highly Accurate Predictions of Missing User Preferences 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2021, 页码: 13
作者:  Shang, Mingsheng;  Yuan, Ye;  Luo, Xin;  Zhou, MengChu
收藏  |  浏览/下载：52/0  |  提交时间：2022/08/22
Computational modeling  Sparse matrices  Convergence  Data models  Predictive models  Linear programming  Euclidean distance  -divergence  big data  convergence analysis  high-dimensional and sparse (HiDS) data  momentum  machine learning  missing data estimation  non-negative latent factor analysis (NLFA)  recommender system (RS)  
Hyper-parameter-evolutionary latent factor analysis for high-dimensional and sparse data from recommender systems 期刊论文
NEUROCOMPUTING, 2021, 卷号: 421, 页码: 316-328
作者:  Chen, Jiufang;  Yuan, Ye;  Ruan, Tao;  Chen, Jia;  Luo, Xin
收藏  |  浏览/下载：74/0  |  提交时间：2021/02/24
Big Data  Intelligent Computation  Latent Factor Analysis  Evolutionary Computing  Learning Algorithm  High-dimensional and Sparse Data  Parameter Free  
randomizedlatentfactormodelforhighdimensionalandsparsematricesfromindustrialapplications 期刊论文
自动化学报英文版, 2019, 卷号: 000, 期号: 001, 页码: 131
作者:  Mingsheng Shang;  Xin Luo;  Zhigang Liu;  Jia Chen;  Ye Yuan;  MengChu Zhou
收藏  |  浏览/下载：109/0  |  提交时间：2019/12/03
An adaptive latent factor model via particle swarm optimization for high-dimensional and sparse matrices 会议论文
2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019, Bari, Italy, October 6, 2019 - October 9, 2019
作者:  Chen, Sili;  Yuan, Ye;  Wang, Jin
收藏  |  浏览/下载：146/0  |  提交时间：2020/02/18
Effects of preprocessing and training biases in latent factor models for recommender systems 期刊论文
NEUROCOMPUTING, 2018, 卷号: 275, 页码: 2019-2030
作者:  Yuan, Ye;  Luo, Xin;  Shang, Ming-Sheng
收藏  |  浏览/下载：95/0  |  提交时间：2018/03/05
Performance of nonnegative latent factor models with β-distance functions in recommender systems 会议论文
15th IEEE International Conference on Networking, Sensing and Control, ICNSC 2018, Zhuhai, China, March 27, 2018 - March 29, 2018
作者:  Yuan, Ye;  Luo, Xin
收藏  |  浏览/下载：101/0  |  提交时间：2019/06/25
Effect of linear biases in latent factor models on high-dimensional and sparse matrices from recommender systems 会议论文
14th IEEE International Conference on Networking, Sensing and Control, ICNSC 2017, Calabria, Italy, May 16, 2017 - May 18, 2017
作者:  Yuan, Ye;  Luo, Xin;  Shang, Ming-Sheng;  Cai, Xin-Yi
Adobe PDF(717Kb)  |  收藏  |  浏览/下载：110/0  |  提交时间：2018/03/16