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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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发表日期:2021
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Dynamical Conventional Neural Network Channel Pruning by Genetic Wavelet Channel Search for Image Classification
期刊论文
FRONTIERS IN COMPUTATIONAL NEUROSCIENCE, 2021, 卷号: 15, 页码: 11
作者:
Chen, Lin
;
Gong, Saijun
;
Shi, Xiaoyu
;
Shang, Mingsheng
收藏
  |  
浏览/下载:79/0
  |  
提交时间:2021/12/28
neural network pruning
neural architecture search
wavelet features
neural network compression
image classification
Multi-robot competitive tracking based on k-WTA neural network with one single neuron
期刊论文
NEUROCOMPUTING, 2021, 卷号: 460, 页码: 1-8
作者:
Peng, Bo
;
Jin, Long
;
Shang, Mingsheng
收藏
  |  
浏览/下载:71/0
  |  
提交时间:2021/11/26
Target tracking
k-winners-take-all
Recurrent neural networks
Finite-time convergence
Global stability
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
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  |  
浏览/下载:130/0
  |  
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
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  |  
浏览/下载:204/0
  |  
提交时间:2021/08/20
Big data
deep model
high-dimensional and sparse (HiDS) matrix
latent factor (LF) analysis
recommender system (RS)
The Stock Market Model with Delayed Information Impact from a Socioeconomic View
期刊论文
ENTROPY, 2021, 卷号: 23, 期号: 7, 页码: 11
作者:
Wang, Zhiting
;
Shi, Guiyuan
;
Shang, Mingsheng
;
Zhang, Yuxia
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  |  
浏览/下载:155/0
  |  
提交时间:2021/08/20
econophysics
financial complexity
collective intelligence
emergent property
stock correlation
detrended cross-correlation analysis
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
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  |  
浏览/下载:82/0
  |  
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
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  |  
浏览/下载:42/0
  |  
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)
Lower limb movement intention recognition for rehabilitation robot aided with projected recurrent neural network
期刊论文
COMPLEX & INTELLIGENT SYSTEMS, 2021, 页码: 12
作者:
Liu, Mei
;
Peng, Bo
;
Shang, Mingsheng
收藏
  |  
浏览/下载:123/0
  |  
提交时间:2021/05/17
Projected recurrent neural network (PRNN)
Lower limb movement
Intention recognition
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
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  |  
浏览/下载:148/0
  |  
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
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:55/0
  |  
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)