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Maximum Entropy Policy for Long-Term Fairness in Interactive Recommender Systems 期刊论文
IEEE TRANSACTIONS ON SERVICES COMPUTING, 2024, 卷号: 17, 期号: 3, 页码: 1029-1043
作者:  Shi, Xiaoyu;  Liu, Quanliang;  Xie, Hong;  Bai, Yanan;  Shang, Mingsheng
收藏  |  浏览/下载：7/0  |  提交时间：2024/08/16
Entropy  Recommender systems  Training  Feedback loop  Training data  Robustness  Real-time systems  Long-term fairness  maximum entropy policy  popularity bias  recommender system  reinforcement learning  web services  
Relieving Popularity Bias in Interactive Recommendation: A Diversity-Novelty-Aware Reinforcement Learning Approach 期刊论文
ACM TRANSACTIONS ON INFORMATION SYSTEMS, 2024, 卷号: 42, 期号: 2, 页码: 30
作者:  Shi, Xiaoyu;  Liu, Quanliang;  Xie, Hong;  Wu, Di;  Peng, Bo;  Shang, Mingsheng;  Lian, Defu
收藏  |  浏览/下载：203/0  |  提交时间：2024/04/07
Interactive recommendation  popularity bias  item fairness  reinfor cement learning  
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：21/0  |  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  
Hyperparameter Learning for Deep Learning-Based Recommender Systems 期刊论文
IEEE TRANSACTIONS ON SERVICES COMPUTING, 2023, 卷号: 16, 期号: 4, 页码: 2699-2712
作者:  Wu, Di;  Sun, Bo;  Shang, Mingsheng
收藏  |  浏览/下载：23/0  |  提交时间：2023/12/25
Terms-Deep learning  differential evolution  grid search  hyperparameter tuning  online services  recommender systems  
A Nonlinear PID-Incorporated Adaptive Stochastic Gradient Descent Algorithm for Latent Factor Analysis 期刊论文
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2023, 页码: 15
作者:  Li, Jinli;  Luo, Xin;  Yuan, Ye;  Gao, Shangce
收藏  |  浏览/下载：200/0  |  提交时间：2023/12/25
High-dimensional and incomplete data  latent factor analysis  stochastic gradient descent  nonlinear proportional integral derivation  particle swarm optimization  parameter adaptation  
Generalized Nesterov's Acceleration-Incorporated, Non-Negative and Adaptive Latent Factor Analysis 期刊论文
IEEE TRANSACTIONS ON SERVICES COMPUTING, 2022, 卷号: 15, 期号: 5, 页码: 2809-2823
作者:  Luo, Xin;  Zhou, Yue;  Liu, Zhigang;  Hu, Lun;  Zhou, MengChu
收藏  |  浏览/下载：105/0  |  提交时间：2022/12/26
Computational modeling  Acceleration  Sparse matrices  Adaptation models  Training  Data models  Convergence  Services computing  service application  big data  latent factor analysis  non-negative latent factor model  high-dimensional and sparse matrix  recommender system  missing data  
Large-Scale and Scalable Latent Factor Analysis via Distributed Alternative Stochastic Gradient Descent for Recommender Systems 期刊论文
IEEE TRANSACTIONS ON BIG DATA, 2022, 卷号: 8, 期号: 2, 页码: 420-431
作者:  Shi, Xiaoyu;  He, Qiang;  Luo, Xin;  Bai, Yanan;  Shang, Mingsheng
收藏  |  浏览/下载：88/0  |  提交时间：2022/08/22
Recommender systems  Training  Optimization  Big Data  Cloud computing  Computational modeling  Sparse matrices  Recommender system  latent factor analysis  high-dimensional and sparse matrices  alternative stochastic gradient descent  distributed computing  
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：140/0  |  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 Deep Latent Factor Model for High-Dimensional and Sparse Matrices in Recommender Systems 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 卷号: 51, 期号: 7, 页码: 4285-4296
作者:  Wu, Di;  Luo, Xin;  Shang, Mingsheng;  He, Yi;  Wang, Guoyin;  Zhou, MengChu
收藏  |  浏览/下载：218/0  |  提交时间：2021/08/20
Big data  deep model  high-dimensional and sparse (HiDS) matrix  latent factor (LF) analysis  recommender system (RS)  
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：91/0  |  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