大数据挖掘与分析

推荐系统

社会网络分析

高维稀疏数据分析

   

081203-计算机应用技术
081202-计算机软件与理论

大数据智能计算

2005-09--2011-01   北京航空航天大学   博士
2001-09--2005-06   电子科技大学   本科

   

2014-02~2017-12,香港理工大学, 博士后、研究助理
2011-01~2014-01,重庆大学, 博士后

2017-10-01-今,国际期刊编委, IEEE/CAA Journal on Automatic Sinica AE
2017-05-31-今,国际期刊编委, IEEE Access AE
2017-03-31-今,IEEE学会高级会员, IEEE Senior Member
2016-12-31-今,国际期刊编委, Neurocomptuing AE
2012-12-31-今,国际期刊编委, Frontiers of Computer Sciences 青年AE

JAVA程序设计
算法分析与设计

   

（1） 重庆市自然科学奖, 三等奖, 省级, 2017
（2） ACM中国学术新星重庆分会奖, 一等奖, 省级, 2015
（3） 重庆市青年科技人才奖, 一等奖, 省级, 2014
（4） 重庆市科技进步奖, 二等奖, 省级, 2012

[1] 罗辛, 李东扬, 吴迪, 袁野. 基于后邻域正则化的联网服务质量隐特征提取装置与方法. CN: CN112866037A, 2021-05-28.
[2] 刘娟, 罗辛, 程雪峰, 黄学达. 基于大数据技术的托辊故障诊断方法、系统及存储介质. CN: CN112660746A, 2021-04-16.
[3] 刘娟, 罗辛, 程雪峰, 黄学达. 托辊故障智能诊断方法、系统及可读存储介质. CN: CN112660745A, 2021-04-16.
[4] 金龙, 罗辛, 齐一萌. 一种多重信息约束下的多智能体一致性协同控制方法. CN: CN112596395A, 2021-04-02.
[5] 刘娟, 罗辛, 程雪峰, 黄学达. 基于机器学习的托辊故障诊断方法、系统及存储介质. CN: CN112504673A, 2021-03-16.
[6] 袁野, 罗辛, 吴昊. 一种基于广义动量的产品智能推荐装置和方法. CN: CN112258263A, 2021-01-22.
[7] 许明, 周玥, 罗辛. 一种基于大数据的个性化金融服务推荐装置和方法. CN: CN112214668A, 2021-01-12.
[8] 张能峰, 吴昊, 罗辛. 一种基于时间序列的金融服务个性化推荐装置和方法. CN: CN112182395A, 2021-01-05.
[9] 许明, 刘志刚, 罗辛. 一种基于网络表示学习的老人看护装置与方法. CN: CN112182498A, 2021-01-05.
[10] 张能锋, 李卿, 罗辛. 一种基于支持向量机的阿尔兹海默症检测装置. CN: CN112155550A, 2021-01-01.
[11] 袁野, 李超华, 罗辛, 尚明生, 吴迪. 一种视频数据线性偏差主特征提取装置和方法. CN: CN107808163B, 2020-12-29.
[12] 袁野, 许明, 罗辛, 尚明生. 一种Web服务吞吐量时变隐特征分析装置和方法. CN: CN112131080A, 2020-12-25.
[13] 袁野, 罗辛, 尚明生, 吴迪. 一种视频数据多维非负隐特征的提取装置和方法. CN: CN107704830B, 2020-12-08.
[14] 张能锋, 袁野, 罗辛, 尚明生. 一种基于多层随机隐特征模型的网页广告投放装置和方法. CN: CN112036963A, 2020-12-04.
[15] 罗辛, 吴昊, 陈敏治, 尚明生, 刘志刚, 钟裕荣. 一种基于偏置张量分解的云服务响应时间预测方法和装置. CN: CN110113180A, 2019-08-09.
[16] 罗辛, 吴昊, 尚明生, 陈敏治, 钟裕荣, 王德贤. 一种时序网络动态隐特征抽取方法和装置. CN: CN110083631A, 2019-08-02.
[17] 许明, 罗辛, 张能锋, 袁野, 吴迪, 夏云霓. 一种基于非负交替方向变换的用户特征抽取方法及抽取装置. 中国: CN104636486B, 2018-01-02.
[18] 吴迪, 李超华, 尚明生, 罗辛, 袁野. 一种基于数据密度峰值的自标记半监督分类方法及装置. 中国: CN106778859A, 2017-05-31.
[19] 史晓雨, 尚明生, 田文洪, 罗辛. 一种能耗感知的云计算服务器资源在线管理方法和系统. 中国: CN106648890A, 2017-05-10.

   

[1] Li, Zhibin, Li, Shuai, Bamasag, Omaimah Omar, Alhothali, Areej, Luo, Xin. Diversified Regularization Enhanced Training for Effective Manipulator Calibration. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS. 2022, [2] Jin, Long, Liang, Siqi, Luo, Xin, Zhou, Mengchu. Distributed and Time-Delayed k-Winner-Take-All Network for Competitive Coordination of Multiple Robots. IEEE TRANSACTIONS ON CYBERNETICS. 2022, [3] 罗辛. Non-negative Latent Factor Analysis-Incorporated and Feature-Weighted Fuzzy Double c-Means Clustering for Incomplete Data. IEEE Transactions on Fuzzy Systems[J]. 2022, [4] Hu, Lun, Yang, Shicheng, Luo, Xin, Yuan, Huaqiang, Sedraoui, Khaled, Zhou, MengChu. A Distributed Framework for Large-scale Protein-protein Interaction Data Analysis and Prediction Using MapReduce. IEEE-CAA JOURNAL OF AUTOMATICA SINICA[J]. 2022, 9(1): 160-172, [5] 罗辛. Multi-Constrained Embedding for Accurate Community Detection on Undirected Networks. IEEE Transactions on Network Science and Engineering[J]. 2022, [6] Jin, Long, Zheng, Xin, Luo, Xin. Neural Dynamics for Distributed Collaborative Control of Manipulators With Time Delays. IEEE-CAA JOURNAL OF AUTOMATICA SINICA[J]. 2022, 9(5): 854-863, [7] Xie, Zhengtai, Jin, Long, Luo, Xin, Li, Shuai, Xiao, Xiuchun. A Data-Driven Cyclic-Motion Generation Scheme for Kinematic Control of Redundant Manipulators. IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY[J]. 2021, 29(1): 53-63, https://www.webofscience.com/wos/woscc/full-record/WOS:000600848100005.
[8] Xin Luo. Large-Scale Affine Matrix Rank Minimization with a Novel Nonconvex Regularizer. IEEE Transactions on Neural Networks and Learning Systems. 2021, [9] Luo, Xin, Liu, Zhigang, Shang, Mingsheng, Lou, Jungang, Zhou, MengChu. Highly-Accurate Community Detection via Pointwise Mutual Information-Incorporated Symmetric Non-Negative Matrix Factorization. IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING[J]. 2021, 8(1): 463-476, https://www.webofscience.com/wos/woscc/full-record/WOS:000631202700037.
[10] Luo, Xin, Liu, Zhigang, Li, Shuai, Shang, Mingsheng, Wang, Zidong. A Fast Non-Negative Latent Factor Model Based on Generalized Momentum Method. IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS[J]. 2021, 51(1): 610-620, http://dx.doi.org/10.1109/TSMC.2018.2875452.
[11] Xin, Luo, Yuan, Ye, Zhou, MengChu, Liu, Zhigang, Shang, Mingsheng. Non-Negative Latent Factor Model Based on beta-Divergence for Recommender Systems. IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS[J]. 2021, 51(8): 4612-4623, [12] Wu, Di, Luo, Xin, Shang, Mingsheng, He, Yi, Wang, Guoyin, Zhou, MengChu. A Deep Latent Factor Model for High-Dimensional and Sparse Matrices in Recommender Systems. IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS[J]. 2021, 51(7): 4285-4296, http://dx.doi.org/10.1109/TSMC.2019.2931393.
[13] Xin Luo. A Novel Approximate Spectral Clustering Algorithm with Dense Cores and Density Peaks. IEEE Transactions on System Man Cybernetics: Systems. 2021, [14] Xin Luo. An L1-and-L2-norm-oriented Latent Factor Model for Recommender Systems. IEEE Transactions on Neural Networks and Learning Systems. 2021, [15] Luo, Xin, Qin, Wen, Dong, Ani, Sedraoui, Khaled, Zhou, MengChu. Efficient and High-quality Recommendations via Momentum-incorporated Parallel Stochastic Gradient Descent-Based Learning. IEEE-CAA JOURNAL OF AUTOMATICA SINICA[J]. 2021, 8(2): 402-411, http://lib.cqvip.com/Qikan/Article/Detail?id=7104122212.
[16] Xin Luo. Robust k-WTA Network Generation, Analysis, and Applications to Multi-Agent Coordination. IEEE Transactions on Cybernetics. 2021, [17] Luo, Xin, Wang, Dexian, Zhou, MengChu, Yuan, Huaqiang. Latent Factor-Based Recommenders Relying on Extended Stochastic Gradient Descent Algorithms. IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS[J]. 2021, 51(2): 916-926, http://dx.doi.org/10.1109/TSMC.2018.2884191.
[18] 罗辛. A Novel Approach to Nonlinear Canonical Polyadic Decomposition on High-Dimensional Incomplete Tensors. IEEE Transactions on Knowledge and Data Engineering[J]. 2021, [19] Luo, Xin, Zhou, Mengchu, Li, Shuai, Wu, Di, Liu, Zhigang, Shang, Mingsheng. Algorithms of Unconstrained Non-Negative Latent Factor Analysis for Recommender Systems. IEEE TRANSACTIONS ON BIG DATA[J]. 2021, 7(1): 227-240, http://dx.doi.org/10.1109/TBDATA.2019.2916868.
[20] Jin, Long, Zhang, Jiazheng, Luo, Xin, Liu, Mei, Li, Shuai, Xiao, Lin, Yang, Zihao. Perturbed Manipulability Optimization in a Distributed Network of Redundant Robots. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS[J]. 2021, 68(8): 7209-7220, http://dx.doi.org/10.1109/TIE.2020.3007099.
[21] Chen, Jiufang, Yuan, Ye, Ruan, Tao, Chen, Jia, Luo, Xin. Hyper-parameter-evolutionary latent factor analysis for high-dimensional and sparse data from recommender systems. NEUROCOMPUTING[J]. 2021, 421: 316-328, https://www.webofscience.com/wos/woscc/full-record/WOS:000593102500011.
[22] Li, Zhibin, Li, Shuai, Luo, Xin. An overview of calibration technology of industrial robots. IEEE-CAA JOURNAL OF AUTOMATICA SINICA[J]. 2021, 8(1): 23-36, http://dx.doi.org/10.1109/JAS.2020.1003381.
[23] Xin Luo. Generalized Nesterov’s Acceleration-incorporated, Non-negative and Adaptive Latent Factor Analysis. IEEE Transactions on Services Computing. 2021, [24] Luo, Xin, Wang, Zidong, Shang, Mingsheng. An Instance-Frequency-Weighted Regularization Scheme for Non-Negative Latent Factor Analysis on High-Dimensional and Sparse Data. IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS[J]. 2021, 51(6): 3522-3532, http://dx.doi.org/10.1109/TSMC.2019.2930525.
[25] Liu, Zhigang, Luo, Xin, Wang, Zidong. Convergence Analysis of Single Latent Factor-Dependent, Nonnegative, and Multiplicative Update-Based Nonnegative Latent Factor Models. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS[J]. 2021, 32(4): 1737-1749, http://dx.doi.org/10.1109/TNNLS.2020.2990990.
[26] Li, Jinli, Yuan, Ye, Ruan, Tao, Chen, Jia, Luo, Xin. A proportional-integral-derivative-incorporated stochastic gradient descent-based latent factor analysis model. NEUROCOMPUTING[J]. 2021, 427: 29-39, http://dx.doi.org/10.1016/j.neucom.2020.11.029.
[27] Ming-Sheng Shang. A Multilayered-and-Randomized Latent Factor Model for High-Dimensional and Sparse Matrices. IEEE Transactions on Big Data. 2020, [28] Ming-Sheng Shang. Large-scale and Scalable Latent Factor Analysis via Distributed Alternative Stochastic Gradient Descent for Recommender Systems. IEEE Transaction on Big Data. 2020, [29] Xin Luo. Temporal Web Service QoS Prediction via Kalman Filter-Incorporated Dynamic Latent Factor Analysis. ECAI 2020. 2020, [30] Ming-Sheng Shang. A Generalized and Fast-converging Non-negative Latent Factor Model for Predicting User Preferences in Recommender Systems. WWW 2020. 2020, [31] Xin Luo. Assimilating Second-Order Information for Building Non-Negative Latent Factor Analysis-Based Recommenders. IEEE Transactions on System Man Cybernetics: Systems. 2020, [32] Xin Luo. An α-β-divergence-generalized Recommender for Highly-accurate Predictions of Missing User Preferences. IEEE Transactions on Cybernetics. 2020, [33] Ming-Sheng Shang. Momentum-incorporated Symmetric Non-negative Latent Factor Models. IEEE Transactions on Big Data. 2020, [34] Luo, Xin, Wu, Hao, Yuan, Huaqiang, Zhou, MengChu. Temporal Pattern-Aware QoS Prediction via Biased Non-Negative Latent Factorization of Tensors. IEEE TRANSACTIONS ON CYBERNETICS[J]. 2020, 50(5): 1798-1809, http://dx.doi.org/10.1109/TCYB.2019.2903736.
[35] Khan, Ameer Hamza, Li, Shuai, Luo, Xin. Obstacle Avoidance and Tracking Control of Redundant Robotic Manipulator: An RNN-Based Metaheuristic Approach. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS[J]. 2020, 16(7): 4670-4680, https://www.webofscience.com/wos/woscc/full-record/WOS:000522523000034.
[36] Ming-Sheng Shang. A Data-Characteristic-Aware Latent Factor Model for Web Services QoS Prediction. IEEE Transactions on Knowledge and Data Engineering. 2020, [37] Xin Luo. Robust Latent Factor Analysis for Precise Represen-tation of High-dimensional and Sparse Data. IEEE/CAA Journal of Automatica Sinica. 2020, [38] Xin Luo. Advancing Non-negative Latent Factorization of Tensors with Diversified Regularizations. IEEE Transactions on Services Computing. 2020, [39] Wu, Di, Jin, Long, Luo, Xin, Plant, C, Wang, H, Cuzzocrea, A, Zaniolo, C, Wu, X. PMLF: Prediction-Sampling-based Multilayer-Structured Latent Factor Analysis. 20TH IEEE INTERNATIONAL CONFERENCE ON DATA MINING (ICDM 2020)null. 2020, 671-680, [40] Song, Yan, Li, Ming, Luo, Xin, Yang, Guisong, Wang, Chongjing. Improved Symmetric and Nonnegative Matrix Factorization Models for Undirected, Sparse and Large-Scaled Networks: A Triple Factorization-Based Approach. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS[J]. 2020, 16(5): 3006-3017, https://www.webofscience.com/wos/woscc/full-record/WOS:000519588700013.
[41] Xin Luo. Symmetric Non-negative Matrix Factorization-based Community Detection Models and Their Convergence Analysis. IEEE Transactions on Neural Networks and Learning Systems. 2020, [42] Xin Luo. Adjusting Learning Depth in Non-negative Latent Factorization of Tensors for Accurately Modeling Temporal Patterns in Dynamic QoS Data. IEEE Transactions on Automation Science and Engineering. 2020, [43] Xin Luo. Reliability-Aware and Deadline-Constrained Mobile Service Composition Over Opportunistic Networks.. IEEE Transactions on Automation Science and Engineering. 2020, [44] Xin Luo. An Algorithm of Inductively Identifying Clusters from Attributed Graphs. IEEE Transactions on Big Data. 2020, [45] Li, Weiling, Luo, Xin, Plant, C, Wang, H, Cuzzocrea, A, Zaniolo, C, Wu, X. A Generalized-Momentum-Accelerated Hessian-Vector Algorithm for High-Dimensional and Sparse Data. 20TH IEEE INTERNATIONAL CONFERENCE ON DATA MINING (ICDM 2020)null. 2020, 1112-1117, [46] Luo, Xin, Zhou, MengChu, Li, Shuai, Hu, Lun, Shang, Mingsheng. Non-Negativity Constrained Missing Data Estimation for High-Dimensional and Sparse Matrices from Industrial Applications. IEEE TRANSACTIONS ON CYBERNETICS[J]. 2020, 50(5): 1844-1855, http://dx.doi.org/10.1109/TCYB.2019.2894283.
[47] Hu, Lun, Hu, Pengwei, Luo, Xin, Yuan, Xiaohui, You, ZhuHong. Incorporating the Coevolving Information of Substrates in Predicting HIV-1 Protease Cleavage Sites. IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS[J]. 2020, 17(6): 2017-2028, https://www.webofscience.com/wos/woscc/full-record/WOS:000597841800017.
[48] Xin Luo. Position-Transitional Particle Swarm Optimization-Incorporated Latent Factor Analysis,. IEEE Transactions on Knowledge and Data Engineering. 2020, [49] Chen, Dechao, Li, Shuai, Wu, Qing, Luo, Xin. New Disturbance Rejection Constraint for Redundant Robot Manipulators: An Optimization Perspective. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS[J]. 2020, 16(4): 2221-2232, https://www.webofscience.com/wos/woscc/full-record/WOS:000510901000006.
[50] Xin Luo. Recurrent Neural Dynamics Models for Perturbed Nonstationary Quadratic Programs: A Control-theoretical Perspective. IEEE Transactions on Neural Networks and Learning Systems. 2020, [51] Xin Luo. RNN for Repetitive Motion Generation of Redundant Robot Manipulators: An Orthogonal Projection Based Scheme. IEEE Transactions on Neural Networks and Learning Systems. 2020, [52] Gan, Zhenhua, Zou, Fumin, Zeng, Nianyin, Xiong, Baoping, Liao, Lyuchao, Li, Han, Luo, Xin, Du, Min. Wavelet Denoising Algorithm Based on NDOA Compressed Sensing for Fluorescence Image of Microarray. IEEE ACCESS[J]. 2019, 7: 13338-13346, http://119.78.100.138/handle/2HOD01W0/7456.
[53] Wang, Dexian, Chen, Yanbin, Guo, Junxiao, Shi, Xiaoyu, He, Chunlin, Luo, Xin, Yuan, Huaqiang. Elastic-net regularized latent factor analysis-based models for recommender systems. NEUROCOMPUTING[J]. 2019, 329: 66-74, http://119.78.100.138/handle/2HOD01W0/7197.
[54] Mingsheng Shang, Xin Luo, Zhigang Liu, Jia Chen, Ye Yuan, MengChu Zhou. Randomized Latent Factor Model for High-dimensional and Sparse Matrices from Industrial Applications. 自动化学报:英文版. 2019, 131-141, http://lib.cqvip.com/Qikan/Article/Detail?id=90687266504849574849484949.
[55] Hu, Lun, Yuan, Xiaohui, Liu, Xing, Xiong, Shengwu, Luo, Xin. Efficiently Detecting Protein Complexes from Protein Interaction Networks via Alternating Direction Method of Multipliers. IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS[J]. 2019, 16(6): 1922-1935, [56] Xin Luo. An Effective QoS Estimating Scheme via Alternating Direction Method-based Matrix Factorization. IEEE Transactions on Services Computing. 2019, [57] Wang, Qingxian, Chen, Sili, Luo, Xin. An adaptive latent factor model via particle swarm optimization. NEUROCOMPUTING[J]. 2019, 369: 176-184, http://dx.doi.org/10.1016/j.neucom.2019.08.052.
[58] Shang, Mingsheng, Luo, Xin, Liu, Zhigang, Chen, Jia, Yuan, Ye, Zhou, MengChu. Randomized Latent Factor Model for High-dimensional and Sparse Matrices from Industrial Applications. IEEE-CAA JOURNAL OF AUTOMATICA SINICA[J]. 2019, 6(1): 131-141, http://lib.cqvip.com/Qikan/Article/Detail?id=90687266504849574849484949.
[59] Ming-Sheng Shang. A Posterior-neighborhood-regularized Latent Factor Model for Highly Accurate Web Service QoS Prediction. IEEE Transactions on Services Computing. 2019, [60] Xin Luo. Incorporating the Coevolving Information of Substrates in Predicting HIV-1 Protease Cleavage Sites.. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2019, [61] Wang, Qingxian, Chen, Minzhi, Shang, Mingsheng, Luo, Xin. A momentum-incorporated latent factorization of tensors model for temporal-aware QoS missing data prediction. NEUROCOMPUTING[J]. 2019, 367: 299-307, http://dx.doi.org/10.1016/j.neucom.2019.08.026.
[62] Luo, Xin, Zhou, Mengchu, Wang, Zidong, Xia, Yunni, Zhu, Qingsheng. An Effective Scheme for QoS Estimation via Alternating Direction Method-Based Matrix Factorization. IEEE TRANSACTIONS ON SERVICES COMPUTING[J]. 2019, 12(4): 503-518, http://dx.doi.org/10.1109/TSC.2016.2597829.
[63] Zeng, Nianyin, Li, Han, Li, Yurong, Luo, Xin. Quantitative Analysis of Immunochromatographic Strip Based on Convolutional Neural Network. IEEE ACCESS[J]. 2019, 7: 16257-16263, https://doaj.org/article/931f9fa432114cb6ad6ebe71808f343e.
[64] Luo, Xin, Zhou, MengChu. Effects of Extended Stochastic Gradient Descent Algorithms on Improving Latent Factor-Based Recommender Systems. IEEE ROBOTICS AND AUTOMATION LETTERS[J]. 2019, 4(2): 618-624, [65] Lu, Huiyan, Jin, Long, Luo, Xin, Liao, Bolin, Guo, Dongsheng, Xiao, Lin. RNN for Solving Perturbed Time-Varying Underdetermined Linear System With Double Bound Limits on Residual Errors and State Variables. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS[J]. 2019, 15(11): 5931-5942, [66] Luo, Xin, Zhou, MengChu, Reveliotis, S, Cappelleri, D, Dimarogonas, DV, Dotoli, M, Fanti, MP, Li, J, Lucena, V, Seatu, C, Xie, X, Zhu, K. Unconstrained Non-negative Factorization of High-dimensional and Sparse Matrices in Recommender Systems. 2018 IEEE 14TH INTERNATIONAL CONFERENCE ON AUTOMATION SCIENCE AND ENGINEERING (CASE)null. 2018, 1406-1413, [67] Luo, Xin, Zhou, MengChu, Li, Shuai, Xia, Yunni, You, ZhuHong, Zhu, QingSheng, Leung, Hareton. Incorporation of Efficient Second-Order Solvers Into Latent Factor Models for Accurate Prediction of Missing QoS Data. IEEE TRANSACTIONS ON CYBERNETICS[J]. 2018, 48(4): 1216-1228, https://www.webofscience.com/wos/woscc/full-record/WOS:000427426000009.
[68] Yuan, Ye, Luo, Xin, Shang, MingSheng. Effects of preprocessing and training biases in latent factor models for recommender systems. NEUROCOMPUTING[J]. 2018, 275: 2019-2030, http://dx.doi.org/10.1016/j.neucom.2017.10.040.
[69] Chen Jia, Luo Xin. Randomized latent factor model for high-dimensional and sparse matrices from industrial applications. 15th IEEE International Conference on Networking, Sensing and Control, ICNSC 2018null. 2018, 1-7, http://119.78.100.138/handle/2HOD01W0/7971.
[70] Jin, Long, Li, Shuai, Luo, Xin, Li, Yangming, Qin, Bin. Neural Dynamics for Cooperative Control of Redundant Robot Manipulators. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS[J]. 2018, 14(9): 3812-3821, https://www.webofscience.com/wos/woscc/full-record/WOS:000443994500003.
[71] Yuan Ye, Luo Xin. Performance of nonnegative latent factor models with β-distance functions in recommender systems. 15th IEEE International Conference on Networking, Sensing and Control, ICNSC 2018null. 2018, 1-7, http://119.78.100.138/handle/2HOD01W0/7960.
[72] Wu, Di, Luo, Xin, Wang, Guoyin, Shang, Mingsheng, Yuan, Ye, Yan, Huyong. A Highly Accurate Framework for Self-Labeled Semisupervised Classification in Industrial Applications. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS[J]. 2018, 14(3): 909-920, http://dx.doi.org/10.1109/TII.2017.2737827.
[73] Luo, Xin, Zhou, MengChu, Li, Shuai, Shang, MingSheng. An Inherently Nonnegative Latent Factor Model for High-Dimensional and Sparse Matrices from Industrial Applications. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS[J]. 2018, 14(5): 2011-2022, http://119.78.100.138/handle/2HOD01W0/8021.
[74] Wang, QingXian, Luo, Xin, Li, Yan, Shi, XiaoYu, Gu, Liang, Shang, MingSheng. Incremental Slope-one recommenders. NEUROCOMPUTING[J]. 2018, 272: 606-618, http://dx.doi.org/10.1016/j.neucom.2017.07.033.
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