中国科学院重庆绿色智能技术研究院机构知识库

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发表日期：2021

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	cuSCNN: A Secure and Batch-Processing Framework for Privacy-Preserving Convolutional Neural Network Prediction on GPU 期刊论文 FRONTIERS IN COMPUTATIONAL NEUROSCIENCE, 2021, 卷号: 15, 页码: 13 作者:  Bai, Yanan;  Liu, Quanliang;  Wu, Wenyuan;  Feng, Yong 收藏  |  浏览/下载：60/0  |  提交时间：2022/08/22 privacy-preserving  convolutional neural network  homomorphic encryption  GPU computation  deep learning  cloud computing
	An Alternating-Direction-Method of Multipliers-Incorporated Approach to Symmetric Non-Negative Latent Factor Analysis 期刊论文 IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 15 作者:  Luo, Xin;  Zhong, Yurong;  Wang, Zidong;  Li, Maozhen 收藏  |  浏览/下载：56/0  |  提交时间：2022/08/22 Symmetric matrices  Computational modeling  Data models  Analytical models  Training  Learning systems  Convergence  Alternating-direction-method of multipliers (ADMM)  learning system  missing data  non-negative latent factor analysis (NLFA)  symmetric high-dimensional and incomplete matrix (SHDI)  undirected weighted network
	Adjusting Learning Depth in Nonnegative Latent Factorization of Tensors for Accurately Modeling Temporal Patterns in Dynamic QoS Data 期刊论文 IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2021, 卷号: 18, 期号: 4, 页码: 2142-2155 作者:  Luo, Xin;  Chen, Minzhi;  Wu, Hao;  Liu, Zhigang;  Yuan, Huaqiang;  Zhou, Mengchu 收藏  |  浏览/下载：83/0  |  提交时间：2021/11/26 Tensors  Data models  Quality of service  Computational modeling  Analytical models  Training  Web services  Algorithm  big data  dynamics  high-dimensional and incomplete (HDI) data  machine learning  missing data estimation  multichannel data  nonnegative latent factorization of tensors (NLFT)  temporal pattern  quality of service (QoS)  web service
	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：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)
	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：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)
	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：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
	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：95/0  |  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：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)
	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：104/0  |  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)
	Hyper-parameter-evolutionary latent factor analysis for high-dimensional and sparse data from recommender systems 期刊论文 NEUROCOMPUTING, 2021, 卷号: 421, 页码: 316-328 作者:  Chen, Jiufang;  Yuan, Ye;  Ruan, Tao;  Chen, Jia;  Luo, Xin 收藏  |  浏览/下载：75/0  |  提交时间：2021/02/24 Big Data  Intelligent Computation  Latent Factor Analysis  Evolutionary Computing  Learning Algorithm  High-dimensional and Sparse Data  Parameter Free