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Adaptively-Accelerated Parallel Stochastic Gradient Descent for High-Dimensional and Incomplete Data Representation Learning 期刊论文
IEEE TRANSACTIONS ON BIG DATA, 2024, 卷号: 10, 期号: 1, 页码: 92-107
作者:  Qin, Wen;  Luo, Xin;  Zhou, Mengchu
收藏  |  浏览/下载：5/0  |  提交时间：2024/05/06
Parallel algorithm  industrial application  latent feature analysis  high-dimensional and incomplete data  stochastic gradient descent  parallelization shared-memory  data science  
Proximal Alternating-Direction-Method-of-Multipliers-Incorporated Nonnegative Latent Factor Analysis 期刊论文
IEEE-CAA JOURNAL OF AUTOMATICA SINICA, 2023, 卷号: 10, 期号: 6, 页码: 1388-1406
作者:  Bi, Fanghui;  Luo, Xin;  Shen, Bo;  Dong, Hongli;  Wang, Zidong
收藏  |  浏览/下载：14/0  |  提交时间：2023/12/25
Data science  high-dimensional and incomplete data  knowledge acquisition  industrial application  nonnegative latent factor analysis(NLFA)  proximal alternating direction method of multipliers  representation learning  
Hierarchical Particle Swarm Optimization-incorporated Latent Factor Analysis for Large-Scale Incomplete Matrices 期刊论文
IEEE TRANSACTIONS ON BIG DATA, 2022, 卷号: 8, 期号: 6, 页码: 1524-1536
作者:  Chen, Jia;  Luo, Xin;  Zhou, Mengchu
收藏  |  浏览/下载：62/0  |  提交时间：2022/12/26
Adaptation models  Optimization  Convergence  Computational modeling  Sparse matrices  Particle swarm optimization  Big Data  Big data  latent factor analysis  particle swarm optimization  high-dimensional and sparse matrix  large-scale incomplete data  missing data estimation  industrial application  
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：130/0  |  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  
An Instance-Frequency-Weighted Regularization Scheme for Non-Negative Latent Factor Analysis on High-Dimensional and Sparse Data 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 卷号: 51, 期号: 6, 页码: 3522-3532
作者:  Luo, Xin;  Wang, Zidong;  Shang, Mingsheng
收藏  |  浏览/下载：81/0  |  提交时间：2021/08/20
High-dimensional and sparse (HiDS) data  industrial application  instance-frequency  non-negative latent factor analysis (NLFA)  recommender system  regularization  
Efficient and High-quality Recommendations via Momentum-incorporated Parallel Stochastic Gradient Descent-Based Learning 期刊论文
IEEE-CAA JOURNAL OF AUTOMATICA SINICA, 2021, 卷号: 8, 期号: 2, 页码: 402-411
作者:  Luo, Xin;  Qin, Wen;  Dong, Ani;  Sedraoui, Khaled;  Zhou, MengChu
收藏  |  浏览/下载：104/0  |  提交时间：2021/03/17
Big data  industrial application  industrial data  latent factor analysis  machine learning  parallel algorithm  recommender system (RS)  stochastic gradient descent (SGD)  
Non-Negativity Constrained Missing Data Estimation for High-Dimensional and Sparse Matrices from Industrial Applications 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2020, 卷号: 50, 期号: 5, 页码: 1844-1855
作者:  Luo, Xin;  Zhou, MengChu;  Li, Shuai;  Hu, Lun;  Shang, Mingsheng
收藏  |  浏览/下载：124/0  |  提交时间：2020/08/24
Computational modeling  Data models  Sparse matrices  Linear programming  Training  Convergence  Analytical models  Alternating-direction-method of multipliers  high-dimensional and sparse matrix  industrial application  non-negative latent factor analysis  recommender system  
A Highly Accurate Framework for Self-Labeled Semisupervised Classification in Industrial Applications 期刊论文
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2018, 卷号: 14, 期号: 3, 页码: 909-920
作者:  Wu, Di;  Luo, Xin;  Wang, Guoyin;  Shang, Mingsheng;  Yuan, Ye;  Yan, Huyong
收藏  |  浏览/下载：213/0  |  提交时间：2018/06/04
Differential evolution (DE)  general framework  industrial application  positioning optimization  self-labeled  semi-supervised classification (SSC)