中国科学院重庆绿色智能技术研究院机构知识库

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	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：127/0  |  提交时间：2024/04/07 Interactive recommendation  popularity bias  item fairness  reinfor cement learning
	Neighbor importance-aware graph collaborative filtering for item recommendation 期刊论文 NEUROCOMPUTING, 2023, 卷号: 549, 页码: 12 作者:  Wang, Qingxian;  Wu, Suqiang;  Bai, Yanan;  Liu, Quanliang;  Shi, Xiaoyu 收藏  |  浏览/下载：10/0  |  提交时间：2023/12/25 Graph neural networks  Recommender system  Node importance  Collaborative filtering  Representation learning
	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：11/0  |  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：181/0  |  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：75/0  |  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：69/0  |  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：128/0  |  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：202/0  |  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：79/0  |  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
	An L-1-and-L-2-Norm-Oriented Latent Factor Model for Recommender Systems 期刊论文 IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 14 作者:  Wu, Di;  Shang, Mingsheng;  Luo, Xin;  Wang, Zidong 收藏  |  浏览/下载：40/0  |  提交时间：2022/08/22 High-dimensional and sparse (HiDS) matrix  latent factor (LF) analysis  L-1 norm  L-2 norm  recommender system (RS)