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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
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Orientation Tracking Incorporated Multicriteria Control for Redundant Manipulators With Dynamic Neural Network
期刊论文
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2024, 卷号: 71, 期号: 4, 页码: 3801-3810
作者:
Liu, Mei
;
Shang, Mingsheng
收藏
  |  
浏览/下载:200/0
  |  
提交时间:2024/01/17
Computational complexity
dynamic neural network (DNN)
kinematic control
multicriteria control scheme
orientation tracking
Combined Physical Process and Deep Learning for Daily Water Level Simulations across Multiple Sites in the Three Gorges Reservoir, China
期刊论文
WATER, 2023, 卷号: 15, 期号: 18, 页码: 16
作者:
Xie, Mingjiang
;
Shan, Kun
;
Zeng, Sidong
;
Wang, Lan
;
Gong, Zhigang
;
Wu, Xuke
;
Yang, Bing
;
Shang, Mingsheng
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  |  
浏览/下载:13/0
  |  
提交时间:2023/12/25
water level prediction
Three Gorges Reservoir
deep learning
hybrid model
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
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  |  
浏览/下载:12/0
  |  
提交时间:2023/12/25
Terms-Deep learning
differential evolution
grid search
hyperparameter tuning
online services
recommender systems
Modeling and Optimization of Sensitivity and Creep for Multi-Component Sensing Materials
期刊论文
NANOMATERIALS, 2023, 卷号: 13, 期号: 2, 页码: 21
作者:
Bi, Gangping
;
Xiao, Bowen
;
Lin, Yuanchang
;
Yan, Shaoqiu
;
Tang, Ying
;
He, Songxiying
;
Shang, Mingsheng
;
He, Guotian
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  |  
浏览/下载:512/0
  |  
提交时间:2023/04/06
RSM
SVR
NSGA-II
MWCNTs
MLG
Ni
magnetic field
sensitivity
creep
A Kalman-Filter-Incorporated Latent Factor Analysis Model for Temporally Dynamic Sparse Data
期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2022, 页码: 14
作者:
Yuan, Ye
;
Luo, Xin
;
Shang, Mingsheng
;
Wang, Zidong
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  |  
浏览/下载:66/0
  |  
提交时间:2022/08/22
Quality of service
Data models
Kalman filters
Estimation
Computational modeling
Web services
Heuristic algorithms
Alternating least squares (ALSs)
computational intelligence
data science
dynamic latent factor analysis (LFA)
dynamics
intelligent computing
Kalman filter
temporal pattern
Web service
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
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  |  
浏览/下载:75/0
  |  
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
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:72/0
  |  
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
Activated Gradients for Deep Neural Networks
期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 13
作者:
Liu, Mei
;
Chen, Liangming
;
Du, Xiaohao
;
Jin, Long
;
Shang, Mingsheng
收藏
  |  
浏览/下载:51/0
  |  
提交时间:2022/08/22
Training
Deep learning
Neural networks
Optimization
Visualization
Newton method
Eigenvalues and eigenfunctions
Exploding gradient problems
gradient activation function (GAF)
ill-conditioned problems
saddle point problems
vanishing gradient problems
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:150/0
  |  
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
Non-Negativity Constrained Missing Data Estimation for High-Dimensional and Sparse Matrices from Industrial Applications
期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2020, 卷号: 50, 期号: 5, 页码: 1844-1855
作者:
Luo, Xin
;
Zhou, MengChu
;
Li, Shuai
;
Hu, Lun
;
Shang, Mingsheng
收藏
  |  
浏览/下载:125/0
  |  
提交时间:2020/08/24
Computational modeling
Data models
Sparse matrices
Linear programming
Training
Convergence
Analytical models
Alternating-direction-method of multipliers
high-dimensional and sparse matrix
industrial application
non-negative latent factor analysis
recommender system