×
验证码:
换一张
忘记密码?
记住我
×
登录
中文版
|
English
中国科学院重庆绿色智能技术研究院机构知识库
KMS Chongqing Institute of Green and Intelligent Technology, CAS
登录
注册
ALL
ORCID
题名
作者
发表日期
学科领域
关键词
文献类型
出处
存缴日期
收录类别
出版者
资助项目
学科门类
学习讨论厅
首页
研究单元&专题
作者
文献类型
学科分类
知识图谱
新闻&公告
在结果中检索
研究单元&专题
作者
罗辛 [10]
尚明生 [7]
吴迪 [4]
袁野 [3]
文献类型
期刊论文 [11]
发表日期
2021 [11]
语种
英语 [11]
出处
IEEE TRANS... [5]
IEEE-CAA J... [2]
IEEE TRANS... [1]
IEEE TRANS... [1]
IEEE TRANS... [1]
NEUROCOMPU... [1]
更多...
资助项目
National ... [11]
Pioneer Hu... [9]
Chongqing ... [6]
Chongqing ... [6]
Chongqing ... [6]
Chongqing ... [6]
更多...
收录类别
SCI [11]
资助机构
×
知识图谱
CSpace
开始提交
已提交作品
待认领作品
已认领作品
未提交全文
收藏管理
QQ客服
官方微博
反馈留言
浏览/检索结果:
共11条,第1-10条
帮助
限定条件
发表日期:2021
资助项目:National Natural Science Foundation of China[61772493]
文献类型:期刊论文
已选(
0
)
清除
条数/页:
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
100
排序方式:
请选择
WOS被引频次升序
WOS被引频次降序
题名升序
题名降序
期刊影响因子升序
期刊影响因子降序
作者升序
作者降序
发表日期升序
发表日期降序
提交时间升序
提交时间降序
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:138/0
  |  
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:215/0
  |  
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:90/0
  |  
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:50/0
  |  
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:92/0
  |  
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:160/0
  |  
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
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:104/0
  |  
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:67/0
  |  
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)
Latent Factor-Based Recommenders Relying on Extended Stochastic Gradient Descent Algorithms
期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 卷号: 51, 期号: 2, 页码: 916-926
作者:
Luo, Xin
;
Wang, Dexian
;
Zhou, MengChu
;
Yuan, Huaqiang
收藏
  |  
浏览/下载:74/0
  |  
提交时间:2021/03/17
Big data
bi-linear
collaborative filtering (CF)
high-dimensional and sparse (HiDS) matrix
industry
latent factor (LF) analysis
missing data
recommender system
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:112/0
  |  
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)