中文版 | English

在结果中检索

CSpace
（本次检索基于用户作品认领结果）

浏览/检索结果: 共6条，第1-6条 帮助

限定条件        
已选(0)清除 条数/页：   排序方式：
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：187/0  |  提交时间：2024/04/07
Interactive recommendation  popularity bias  item fairness  reinfor cement 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 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 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)  
Robust Latent Factor Analysis for Precise Representation of High-Dimensional and Sparse Data 期刊论文
IEEE-CAA JOURNAL OF AUTOMATICA SINICA, 2021, 卷号: 8, 期号: 4, 页码: 796-805
作者:  Wu, Di;  Luo, Xin
收藏  |  浏览/下载：81/0  |  提交时间：2021/05/17
High-dimensional and sparse matrix  L-1-norm  L-2-norm  latent factor model  recommender system  smooth L-1-norm  
Algorithms of Unconstrained Non-Negative Latent Factor Analysis for Recommender Systems 期刊论文
IEEE TRANSACTIONS ON BIG DATA, 2021, 卷号: 7, 期号: 1, 页码: 227-240
作者:  Luo, Xin;  Zhou, Mengchu;  Li, Shuai;  Wu, Di;  Liu, Zhigang;  Shang, Mingsheng
收藏  |  浏览/下载：145/0  |  提交时间：2021/05/17
Data models  Training  Sparse matrices  Recommender systems  Computational modeling  Big Data  Scalability  Non-negative latent factor analysis  non-negativity  latent factor analysis  unconstrained optimization  high-dimensional and sparse matrix  collaborative filtering  recommender system  big data