×
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
大数据挖掘及应用中... [15]
作者
罗辛 [41]
尚明生 [18]
吴迪 [7]
袁野 [5]
史晓雨 [4]
张鹏 [1]
更多...
文献类型
期刊论文 [41]
发表日期
2024 [1]
2023 [3]
2022 [8]
2021 [9]
2020 [4]
2019 [4]
更多...
语种
英语 [41]
出处
NEUROCOMPU... [8]
IEEE TRANS... [5]
IEEE TRANS... [4]
IEEE TRANS... [4]
IEEE TRANS... [3]
IEEE ACCES... [2]
更多...
资助项目
National ... [23]
Pioneer H... [23]
National ... [17]
Chongqing... [10]
Chongqing... [10]
Chongqing... [10]
更多...
收录类别
SCI [41]
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
(本次检索基于用户作品认领结果)
浏览/检索结果:
共41条,第1-10条
帮助
限定条件
收录类别:SCI
语种:英语
作者:罗辛
第一作者
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
A Fast Nonnegative Autoencoder-Based Approach to Latent Feature Analysis on High-Dimensional and Incomplete Data
期刊论文
IEEE TRANSACTIONS ON SERVICES COMPUTING, 2024, 卷号: 17, 期号: 3, 页码: 733-746
作者:
Bi, Fanghui
;
He, Tiantian
;
Luo, Xin
收藏
  |  
浏览/下载:9/0
  |  
提交时间:2024/08/16
Knowledge acquisition
data science
high-dimensional and incomplete data
neural network
fast nonnegative AutoEncoder
latent feature analysis
link prediction
network representation learning
Parallel Adaptive Stochastic Gradient Descent Algorithms for Latent Factor Analysis of High-Dimensional and Incomplete Industrial Data
期刊论文
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2023, 页码: 14
作者:
Qin, Wen
;
Luo, Xin
;
Li, Shuai
;
Zhou, MengChu
收藏
  |  
浏览/下载:27/0
  |  
提交时间:2023/12/25
Adaptation models
Training
Data models
Convergence
Stochastic processes
Sparse matrices
Tuning
Big data
latent factor analysis
Index Terms
adaptive model
parallelization
machine learning
stochastic gradient descent
high-dimensional and incomplete matrix
MNL: A Highly-Efficient Model for Large-scale Dynamic Weighted Directed Network Representation
期刊论文
IEEE TRANSACTIONS ON BIG DATA, 2023, 卷号: 9, 期号: 3, 页码: 889-903
作者:
Chen, Minzhi
;
He, Chunlin
;
Luo, Xin
收藏
  |  
浏览/下载:20/0
  |  
提交时间:2023/12/25
Tensors
Data models
Computational modeling
Adaptation models
Analytical models
Big Data
Heuristic algorithms
Dynamic weighted directed network
high-dimensional and incomplete tensor
non-negative latent-factorization-of-tensors
linear bias
high dimensional and incomplete
momentum method
particle swarm optimization
adaptive model
A Double-Space and Double-Norm Ensembled Latent Factor Model for Highly Accurate Web Service QoS Prediction
期刊论文
IEEE TRANSACTIONS ON SERVICES COMPUTING, 2023, 卷号: 16, 期号: 2, 页码: 802-814
作者:
Wu, Di
;
Zhang, Peng
;
He, Yi
;
Luo, Xin
收藏
  |  
浏览/下载:19/0
  |  
提交时间:2023/12/25
Web service
service selection
Quality-of-Service (QoS)
latent factor analysis
missing data prediction
big data
A Novel Approach to Large-Scale Dynamically Weighted Directed Network Representation
期刊论文
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2022, 卷号: 44, 期号: 12, 页码: 9756-9773
作者:
Luo, Xin
;
Wu, Hao
;
Wang, Zhi
;
Wang, Jianjun
;
Meng, Deyu
收藏
  |  
浏览/下载:89/0
  |  
提交时间:2022/12/26
Tensors
Computational modeling
Numerical models
Data models
Convergence
Analytical models
Adaptation models
Dynamically weighted directed network
terminal interaction pattern analysis system
latent factorization of tensors
high dimensional and incomplete tensor
link prediction
representation learning
latent feature
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:102/0
  |  
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
A Data-Characteristic-Aware Latent Factor Model for Web Services QoS Prediction
期刊论文
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2022, 卷号: 34, 期号: 6, 页码: 2525-2538
作者:
Wu, Di
;
Luo, Xin
;
Shang, Mingsheng
;
He, Yi
;
Wang, Guoyin
;
Wu, Xindong
收藏
  |  
浏览/下载:82/0
  |  
提交时间:2022/08/22
Web Service
quality-of-service
QoS
latent factor analysis
density peak
data-characteristic-aware
missing data
big data
topological neighborhood
noise data
service selection
data science
A Multilayered-and-Randomized Latent Factor Model for High-Dimensional and Sparse Matrices
期刊论文
IEEE TRANSACTIONS ON BIG DATA, 2022, 卷号: 8, 期号: 3, 页码: 784-794
作者:
Yuan, Ye
;
He, Qiang
;
Luo, Xin
;
Shang, Mingsheng
收藏
  |  
浏览/下载:88/0
  |  
提交时间:2022/08/22
Computational modeling
Sparse matrices
Big Data
Data models
Stochastic processes
Training
Software algorithms
Big data
latent factor analysis
generally multilayered structure
deep forest
multilayered extreme learning machine
randomized-learning
high-dimensional and sparse matrix
stochastic gradient descent
randomized model
Advancing Non-Negative Latent Factorization of Tensors With Diversified Regularization Schemes
期刊论文
IEEE TRANSACTIONS ON SERVICES COMPUTING, 2022, 卷号: 15, 期号: 3, 页码: 1334-1344
作者:
Wu, Hao
;
Luo, Xin
;
Zhou, Mengchu
收藏
  |  
浏览/下载:74/0
  |  
提交时间:2022/08/22
High-dimensional and sparse tensor
missing data
latent factor analysis
temporal pattern
non-negativity
non-negative latent factorization of tensor
regularization
ensemble
services computing
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:84/0
  |  
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