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ORCIDMingsheng Shang 0001
Ming-Sheng Shang 0001
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- affiliation: Chinese Academy of Sciences, Chongqing Institute of Green and Intelligent Technology, Chongqing, China
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2020 – today
- 2024
[j70]Dexiu Ma
, Mei Liu, Mingsheng Shang:
Neural dynamics solver for time-dependent infinity-norm optimization based on ACP framework with robot application. Neurocomputing 567: 127032 (2024)- [j69]Haoran Gu, Yunni Xia, Hong Xie, Xiaoyu Shi, Mingsheng Shang:
Robust and efficient algorithms for conversational contextual bandit. Inf. Sci. 657: 119993 (2024) - [j68]Tao Tan, Hong Xie, Yunni Xia, Xiaoyu Shi, Mingsheng Shang:
Asynchronous SGD with stale gradient dynamic adjustment for deep learning training. Inf. Sci. 681: 121220 (2024) - [j67]Wei Cui, Xuerui Zhang, Mingsheng Shang:
Multi-modality frequency-aware cross attention network for fake news detection. J. Intell. Fuzzy Syst. 46(1): 433-455 (2024) - [j66]Tao Tan, Hong Xie, Yunni Xia, Xiaoyu Shi, Mingsheng Shang:
Adaptive moving average Q-learning. Knowl. Inf. Syst. 66(12): 7389-7417 (2024) - [j65]Bo Peng, Kefan Zhang, Long Jin, Mingsheng Shang:
A Transfer-Learning-Like Neural Dynamics Algorithm for Arctic Sea Ice Extraction. Neural Process. Lett. 56(4): 221 (2024) - [j64]Mei Liu, Mingsheng Shang:
Orientation Tracking Incorporated Multicriteria Control for Redundant Manipulators With Dynamic Neural Network. IEEE Trans. Ind. Electron. 71(4): 3801-3810 (2024) - [j63]Mei Liu, Fan Zhang, Li He, Mingsheng Shang:
Dynamic Neural Network for Motion/Force Control of Manipulators With Polynomial Noises. IEEE Trans. Ind. Electron. 71(10): 12559-12569 (2024) - [j62]Jiawang Tan, Mingsheng Shang, Long Jin:
Metaheuristic-Based RNN for Manipulability Optimization of Redundant Manipulators. IEEE Trans. Ind. Informatics 20(4): 6489-6498 (2024) - [j61]Mei Liu, Kun Liu, Puchen Zhu, G. Q. (Kouchi) Zhang, Xin Ma, Mingsheng Shang:
Data-Driven Remote Center of Cyclic Motion (RC$^{2}$M) Control for Redundant Robots With Rod-Shaped End-Effector. IEEE Trans. Ind. Informatics 20(4): 6772-6780 (2024) - [j60]Long Jin, Longqi Liu, Xingxia Wang, Mingsheng Shang, Fei-Yue Wang:
Physical-Informed Neural Network for MPC-Based Trajectory Tracking of Vehicles With Noise Considered. IEEE Trans. Intell. Veh. 9(3): 4493-4503 (2024) - [j59]Ying Liufu, Long Jin, Mingsheng Shang, Xingxia Wang, Fei-Yue Wang:
ACP-Incorporated Perturbation-Resistant Neural Dynamics Controller for Autonomous Vehicles. IEEE Trans. Intell. Veh. 9(4): 4675-4686 (2024) - [j58]Hong Xie, Mingze Zhong, Xiaoyu Shi, Xiaoying Zhang, Jiang Zhong, Mingsheng Shang:
Probabilistic Modeling of Assimilate-Contrast Effects in Online Rating Systems. IEEE Trans. Knowl. Data Eng. 36(2): 795-808 (2024) - [j57]Mei Liu, Xiufang Chen, Mingsheng Shang, Hongwei Li:
A Pseudoinversion-Free Method for Weight Updating in Broad Learning System. IEEE Trans. Neural Networks Learn. Syst. 35(2): 2378-2389 (2024) - [j56]Xiaoyu Shi, Quanliang Liu, Hong Xie, Di Wu, Bo Peng, Mingsheng Shang, Defu Lian:
Relieving Popularity Bias in Interactive Recommendation: A Diversity-Novelty-Aware Reinforcement Learning Approach. ACM Trans. Inf. Syst. 42(2): 52:1-52:30 (2024) - [j55]Xiaoyu Shi, Quanliang Liu, Hong Xie, Yanan Bai, Mingsheng Shang:
Maximum Entropy Policy for Long-Term Fairness in Interactive Recommender Systems. IEEE Trans. Serv. Comput. 17(3): 1029-1043 (2024) - [j54]Liangming Chen, Long Jin, Mingsheng Shang, Fei-Yue Wang:
Enhancing Representation Power of Deep Neural Networks With Negligible Parameter Growth for Industrial Applications. IEEE Trans. Syst. Man Cybern. Syst. 54(11): 6837-6848 (2024) - [c51]Chongjun Xia, Xiaoyu Shi, Hong Xie, Quanliang Liu, Mingsheng Shang:
Hierarchical Reinforcement Learning for Long-term Fairness in Interactive Recommendation. ICWS 2024: 300-309 - [c50]Yutong Chen, Hongzuo Xu, Guansong Pang, Hezhe Qiao, Yuan Zhou, Mingsheng Shang:
Self-supervised Spatial-Temporal Normality Learning for Time Series Anomaly Detection. ECML/PKDD (6) 2024: 145-162 - [i17]Yutong Chen, Hongzuo Xu, Guansong Pang, Hezhe Qiao, Yuan Zhou, Mingsheng Shang:
Self-Supervised Spatial-Temporal Normality Learning for Time Series Anomaly Detection. CoRR abs/2406.19770 (2024) - 2023
- [j53]Xiaoyu Xu, Xiaoyu Shi, Mingsheng Shang:
Graph neural networks via contrast between separation and aggregation for self and neighborhood. Expert Syst. Appl. 224: 119994 (2023) - [j52]Bo Peng, Xuerui Zhang, Mingsheng Shang:
A Novel Competition-Based Coordination Model with Dynamic Feedback for Multi-Robot Systems. IEEE CAA J. Autom. Sinica 10(10): 2029-2031 (2023) - [j51]Mei Liu, Huanmei Wu, Mingsheng Shang:
A noise-suppressing discrete-time neural dynamics model for solving time-dependent multi-linear M-tensor equation. Neurocomputing 520: 240-249 (2023) - [j50]Wei Cui, Mingsheng Shang:
KAGN:knowledge-powered attention and graph convolutional networks for social media rumor detection. J. Big Data 10(1): 45 (2023) - [j49]Ye Yuan, Xin Luo, Mingsheng Shang, Zidong Wang:
A Kalman-Filter-Incorporated Latent Factor Analysis Model for Temporally Dynamic Sparse Data. IEEE Trans. Cybern. 53(9): 5788-5801 (2023) - [j48]Mei Liu, Liangming Chen, Xiaohao Du, Long Jin, Mingsheng Shang:
Activated Gradients for Deep Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 34(4): 2156-2168 (2023) - [j47]Mei Liu, Li He, Mingsheng Shang:
Dynamic Neural Network for Bicriteria Weighted Control of Robot Manipulators. IEEE Trans. Neural Networks Learn. Syst. 34(8): 4570-4583 (2023) - [j46]Di Wu, Bo Sun, Mingsheng Shang:
Hyperparameter Learning for Deep Learning-Based Recommender Systems. IEEE Trans. Serv. Comput. 16(4): 2699-2712 (2023) - [j45]Mei Liu, Ying Liufu, Huiyan Lu, Mingsheng Shang:
Neural Solution to Dynamic Overdetermined System With Applications to Data Fitting and Parameters Estimation. IEEE Trans. Syst. Man Cybern. Syst. 53(12): 7330-7341 (2023) - [c49]Kexiang Zeng, Xiaoyu Shi, Hong Xie, Mingsheng Shang:
Contrastive Learning based Item Representation with Asymmetric Augmentation for Sequential Recommendation. ADMIT 2023: 68-73 - [c48]Zhi Qi, Hong Xie, Mingsheng Shang:
A Predictive Coding Approach to Multivariate Time Series Anomaly Detection. DASFAA (1) 2023: 188-204 - [c47]Bingchao Wang, Xiaoyu Shi, Mingsheng Shang:
A Self-decoupled Interpretable Prediction Framework for Highly-Variable Cloud Workloads. DASFAA (1) 2023: 588-603 - [c46]Xiaoyu Shi, Quanliang Liu, Hong Xie, Mingsheng Shang:
Towards Long-term Fairness in Interactive Recommendation: A Maximum Entropy Reinforcement Learning Approach. ICWS 2023: 118-123 - [c45]Jinyu Mo, Hong Xie, Xiaoyu Shi, Mingsheng Shang:
CGCCMR: An Enhanced Multi-gate Model for Cross-Market Recommendation. IJCNN 2023: 1-8 - 2022
- [j44]Xiaoyu Xu, Di Wu, Mingsheng Shang:
A structure-characteristic-aware network embedding model via differential evolution. Expert Syst. Appl. 204: 117611 (2022) - [j43]Mei Liu, Xiaoyan Zhang, Mingsheng Shang, Long Jin:
Gradient-Based Differential $k\text{WTA}$ Network With Application to Competitive Coordination of Multiple Robots. IEEE CAA J. Autom. Sinica 9(8): 1452-1463 (2022) - [j42]Mei Liu, Mingsheng Shang:
On RNN-Based $k$-WTA Models With Time-Dependent Inputs. IEEE CAA J. Autom. Sinica 9(11): 2034-2036 (2022) - [j41]Mei Liu, Jiazheng Zhang, Mingsheng Shang:
Real-time cooperative kinematic control for multiple robots in distributed scenarios with dynamic neural networks. Neurocomputing 491: 621-632 (2022) - [j40]Qing Li, Diwen Xiong, Mingsheng Shang:
Adjusted stochastic gradient descent for latent factor analysis. Inf. Sci. 588: 196-213 (2022) - [j39]Xiaoyu Xu, Guansong Pang, Di Wu, Mingsheng Shang:
Joint hyperbolic and Euclidean geometry contrastive graph neural networks. Inf. Sci. 609: 799-815 (2022) - [j38]Qing Li, Guansong Pang, Mingsheng Shang:
An efficient annealing-assisted differential evolution for multi-parameter adaptive latent factor analysis. J. Big Data 9(1): 95 (2022) - [j37]Lin Chen, Jingkuan Song, Xuerui Zhang, Mingsheng Shang:
MCFL: multi-label contrastive focal loss for deep imbalanced pedestrian attribute recognition. Neural Comput. Appl. 34(19): 16701-16715 (2022) - [j36]Long Jin, Yimeng Qi, Xin Luo, Shuai Li, Mingsheng Shang:
Distributed Competition of Multi-Robot Coordination Under Variable and Switching Topologies. IEEE Trans Autom. Sci. Eng. 19(4): 3575-3586 (2022) - [j35]Xiaoyu Shi, Qiang He, Xin Luo, Yanan Bai, Mingsheng Shang:
Large-Scale and Scalable Latent Factor Analysis via Distributed Alternative Stochastic Gradient Descent for Recommender Systems. IEEE Trans. Big Data 8(2): 420-431 (2022) - [j34]Ye Yuan, Qiang He, Xin Luo, Mingsheng Shang:
A Multilayered-and-Randomized Latent Factor Model for High-Dimensional and Sparse Matrices. IEEE Trans. Big Data 8(3): 784-794 (2022) - [j33]Yurong Zhong, Long Jin, Mingsheng Shang, Xin Luo:
Momentum-Incorporated Symmetric Non-Negative Latent Factor Models. IEEE Trans. Big Data 8(4): 1096-1106 (2022) - [j32]Mingsheng Shang, Ye Yuan, Xin Luo, MengChu Zhou:
An α-β-Divergence-Generalized Recommender for Highly Accurate Predictions of Missing User Preferences. IEEE Trans. Cybern. 52(8): 8006-8018 (2022) - [j31]Mei Liu, Xiaoyan Zhang, Mingsheng Shang:
Computational Neural Dynamics Model for Time-Variant Constrained Nonlinear Optimization Applied to Winner-Take-All Operation. IEEE Trans. Ind. Informatics 18(9): 5936-5948 (2022) - [j30]Di Wu, Xin Luo, Mingsheng Shang, Yi He, Guoyin Wang, Xindong Wu:
A Data-Characteristic-Aware Latent Factor Model for Web Services QoS Prediction. IEEE Trans. Knowl. Data Eng. 34(6): 2525-2538 (2022) - [j29]Di Wu, Mingsheng Shang, Xin Luo, Zidong Wang:
An L1-and-L2-Norm-Oriented Latent Factor Model for Recommender Systems. IEEE Trans. Neural Networks Learn. Syst. 33(10): 5775-5788 (2022) - [j28]Di Wu, Qiang He, Xin Luo, Mingsheng Shang, Yi He, Guoyin Wang:
A Posterior-Neighborhood-Regularized Latent Factor Model for Highly Accurate Web Service QoS Prediction. IEEE Trans. Serv. Comput. 15(2): 793-805 (2022) - [c44]Liangming Chen, Long Jin, Mingsheng Shang:
Zero Stability Well Predicts Performance of Convolutional Neural Networks. AAAI 2022: 6268-6277 - [c43]Bo Sun, Di Wu, Mingsheng Shang, Yi He:
Toward Auto-Learning Hyperparameters for Deep Learning-Based Recommender Systems. DASFAA (2) 2022: 323-331 - [c42]Zihui Zhao, Xiaoyu Shi, Mingsheng Shang:
Performance and Cost-Aware Task Scheduling via Deep Reinforcement Learning in Cloud Environment. ICSOC 2022: 600-615 - [c41]Hao Liu, Hezhe Qiao, Xiaoyu Shi, Mingsheng Shang:
Aspect-aware Asymmetric Representation Learning Network for Review-based Recommendation. IJCNN 2022: 1-8 - [c40]Meijun Luo, Lin Chen, Yunni Xia, Mingsheng Shang:
Attention Auxiliary Spatial Fusion for Pedestrian Attribute Recognition. SMC 2022: 204-209 - [i16]Liangming Chen, Long Jin, Mingsheng Shang:
Zero Stability Well Predicts Performance of Convolutional Neural Networks. CoRR abs/2206.13100 (2022) - 2021
- [j27]Zhiting Wang, Guiyuan Shi, Mingsheng Shang, Yuxia Zhang:
The Stock Market Model with Delayed Information Impact from a Socioeconomic View. Entropy 23(7): 893 (2021) - [j26]Lin Chen, Saijun Gong, Xiaoyu Shi, Mingsheng Shang:
Dynamical Conventional Neural Network Channel Pruning by Genetic Wavelet Channel Search for Image Classification. Frontiers Comput. Neurosci. 15: 760554 (2021) - [j25]Bo Peng, Long Jin, Mingsheng Shang:
Multi-robot competitive tracking based on k-WTA neural network with one single neuron. Neurocomputing 460: 1-8 (2021) - [j24]Qing Li, Mingsheng Shang:
BALFA: A brain storm optimization-based adaptive latent factor analysis model. Inf. Sci. 578: 913-929 (2021) - [j23]Xin Luo, Mengchu Zhou, Shuai Li, Di Wu, Zhigang Liu, Mingsheng Shang:
Algorithms of Unconstrained Non-Negative Latent Factor Analysis for Recommender Systems. IEEE Trans. Big Data 7(1): 227-240 (2021) - [j22]Xin Luo, Zhigang Liu, Mingsheng Shang, Jungang Lou, MengChu Zhou:
Highly-Accurate Community Detection via Pointwise Mutual Information-Incorporated Symmetric Non-Negative Matrix Factorization. IEEE Trans. Netw. Sci. Eng. 8(1): 463-476 (2021) - [j21]Xin Luo, Zhigang Liu, Shuai Li, Mingsheng Shang, Zidong Wang:
A Fast Non-Negative Latent Factor Model Based on Generalized Momentum Method. IEEE Trans. Syst. Man Cybern. Syst. 51(1): 610-620 (2021) - [j20]Xin Luo, Zidong Wang, Mingsheng Shang:
An Instance-Frequency-Weighted Regularization Scheme for Non-Negative Latent Factor Analysis on High-Dimensional and Sparse Data. IEEE Trans. Syst. Man Cybern. Syst. 51(6): 3522-3532 (2021) - [j19]Di Wu, Xin Luo, Mingsheng Shang, Yi He, Guoyin Wang, MengChu Zhou:
A Deep Latent Factor Model for High-Dimensional and Sparse Matrices in Recommender Systems. IEEE Trans. Syst. Man Cybern. Syst. 51(7): 4285-4296 (2021) - [j18]Xin Luo, Ye Yuan, MengChu Zhou, Zhigang Liu, Mingsheng Shang:
Non-Negative Latent Factor Model Based on β-Divergence for Recommender Systems. IEEE Trans. Syst. Man Cybern. Syst. 51(8): 4612-4623 (2021) - [c39]Jianxiong Xu, Xiaoyu Shi, Hezhe Qiao, Mingsheng Shang, Xianbo He, Qingyu He:
UEIN: A User Evolving Interests Network for Click-Through Rate Prediction. BigDataSE 2021: 34-41 - [c38]Diwen Xiong, Mingsheng Shang:
RoboNet: a Neural Network Based Kinematic Parameter Identification Model. ICNSC 2021: 1-6 - [c37]Leming Zhou, Qing Li, Mingsheng Shang:
Chronic Disease Detection Via Non-negative Latent Feature Analysis. ICNSC 2021: 1-6 - [c36]Jiabao Zhong, Hezhe Qiao, Lin Chen, Mingsheng Shang, Qun Liu:
Improving Pedestrian Attribute Recognition with Multi-Scale Spatial Calibration. IJCNN 2021: 1-8 - [i15]Mei Liu, Liangming Chen, Xiaohao Du, Long Jin, Mingsheng Shang:
Activated Gradients for Deep Neural Networks. CoRR abs/2107.04228 (2021) - 2020
- [j17]Xin Luo, Mengchu Zhou, Shuai Li, Lun Hu, Mingsheng Shang:
Non-Negativity Constrained Missing Data Estimation for High-Dimensional and Sparse Matrices from Industrial Applications. IEEE Trans. Cybern. 50(5): 1844-1855 (2020) - [c35]Tao Wang, Xiaoyu Shi, Mingsheng Shang:
Diversity-Aware Top-N Recommendation: A Deep Reinforcement Learning Way. Big Data (CCF) 2020: 226-241 - [c34]Ye Yuan, Mingsheng Shang, Xin Luo:
Temporal Web Service QoS Prediction via Kalman Filter-Incorporated Latent Factor Analysis. ECAI 2020: 561-568 - [c33]Qing Li, Mingsheng Shang:
A Compressed Sensing and Porous 9-7 Wavelet Transform-based Image Fusion Algorithm. SMC 2020: 4185-4191 - [c32]Chonghao Zhao, Xiaoyu Shi, Mingsheng Shang, Yiqiu Fang:
A Clustering-Based Collaborative Filtering Recommendation Algorithm via Deep Learning User Side Information. WISE (2) 2020: 331-342 - [c31]Ye Yuan, Xin Luo, Mingsheng Shang, Di Wu:
A Generalized and Fast-converging Non-negative Latent Factor Model for Predicting User Preferences in Recommender Systems. WWW 2020: 498-507 - [i14]Khushnood Abbas, Alireza Abbasi, Shi Dong, Niu Ling, Mingsheng Shang, Chen Liong, Bolun Chen:
TempNodeEmb: Temporal Node Embedding considering temporal edge influence matrix. CoRR abs/2008.06940 (2020)
2010 – 2019
- 2019
- [j16]Qingxian Wang, Binbin Peng, Xiaoyu Shi, Tianqi Shang, Mingsheng Shang:
DCCR: Deep Collaborative Conjunctive Recommender for Rating Prediction. IEEE Access 7: 60186-60198 (2019) - [j15]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. IEEE CAA J. Autom. Sinica 6(1): 131-141 (2019) - [j14]Qingxian Wang, Minzhi Chen, Mingsheng Shang, Xin Luo:
A momentum-incorporated latent factorization of tensors model for temporal-aware QoS missing data prediction. Neurocomputing 367: 299-307 (2019) - [c30]Di Wu, Yi He, Xin Luo, Mingsheng Shang, Xindong Wu:
Online Feature Selection with Capricious Streaming Features: A General Framework. IEEE BigData 2019: 683-688 - [c29]Longyu Ran, Xiaoyu Shi, Mingsheng Shang:
SLAs-Aware Online Task Scheduling Based on Deep Reinforcement Learning Method in Cloud Environment. HPCC/SmartCity/DSS 2019: 1518-1525 - [c28]Yuanxin Lv, Xiaoyu Shi, Longyu Ran, Mingsheng Shang:
Random Forest-Based Ensemble Estimator for Concrete Compressive Strength Prediction via AdaBoost Method. ICNC-FSKD 2019: 557-565 - [c27]Mengzhen Luo, Xiaoyu Shi, Qianqian Ji, Mingsheng Shang, Xianbo He, Weiguo Tao:
A Deep Self-learning Classification Framework for Incomplete Medical Patents with Multi-label. ICNC-FSKD 2019: 566-573 - [c26]Qianqian Ji, Xiaoyu Shi, Mingsheng Shang:
A Deep Temporal Collaborative Filtering Recommendation Framework via Joint Learning from Long and Short-Term Effects. ISPA/BDCloud/SocialCom/SustainCom 2019: 959-966 - [c25]Di Wu, Xin Luo, Mingsheng Shang, Yi He, Guoyin Wang, Xindong Wu:
A Data-Aware Latent Factor Model for Web Service QoS Prediction. PAKDD (1) 2019: 384-399 - [c24]Jiajia Jiang, Yunni Xia, Mingsheng Shang:
A Fast Autoencoder-based Recommender. SMC 2019: 1732-1737 - 2018
- [j13]Qing-Xian Wang, Xin Luo, Yan Li, Xiao-Yu Shi, Liang Gu, Mingsheng Shang:
Incremental Slope-one recommenders. Neurocomputing 272: 606-618 (2018) - [j12]Di Wu, Mingsheng Shang, Xin Luo, Ji Xu, Huyong Yan, Weihui Deng, Guoyin Wang:
Self-training semi-supervised classification based on density peaks of data. Neurocomputing 275: 180-191 (2018) - [j11]Ye Yuan, Xin Luo, Mingsheng Shang:
Effects of preprocessing and training biases in latent factor models for recommender systems. Neurocomputing 275: 2019-2030 (2018) - [j10]Wenhong Tian, Majun He, Wenxia Guo, Wenqiang Huang, Xiaoyu Shi, Mingsheng Shang, Adel Nadjaran Toosi, Rajkumar Buyya:
On minimizing total energy consumption in the scheduling of virtual machine reservations. J. Netw. Comput. Appl. 113: 64-74 (2018) - [j9]Di Wu, Xin Luo, Guoyin Wang, Mingsheng Shang, Ye Yuan, Huyong Yan:
A Highly Accurate Framework for Self-Labeled Semisupervised Classification in Industrial Applications. IEEE Trans. Ind. Informatics 14(3): 909-920 (2018) - [j8]Xin Luo, MengChu Zhou, Shuai Li, Mingsheng Shang:
An Inherently Nonnegative Latent Factor Model for High-Dimensional and Sparse Matrices from Industrial Applications. IEEE Trans. Ind. Informatics 14(5): 2011-2022 (2018) - [c23]Yelu Mao, Xiaoyu Shi, Mingsheng Shang, Ying Zhang:
TCR: Temporal-CNN for Reviews Based Recommendation System. ICDLT 2018: 71-75 - [c22]Binbin Peng, Lin Chen, Mingsheng Shang, Jianjun Xu:
Fully Convolutional Neural Networks for Tissue Histopathology Image Classification and Segmentation. ICIP 2018: 1403-1407 - [c21]Xiaoyu Shi, Mingsheng Shang, Wenhong Tian, Khushnood Abbas, Shuai Wang, Tianshu Wu:
Autonomic performance management of cloud server based on adaptive control method. ICNSC 2018: 1-6 - [c20]Di Wu, Mingsheng Shang, Guoyin Wang, Li Li:
A self-training semi-supervised classification algorithm based on density peaks of data and differential evolution. ICNSC 2018: 1-6 - [c19]Zhigang Liu, Xin Luo, Shuai Li, Mingsheng Shang:
Accelerated Non-negative Latent Factor Analysis on High-Dimensional and Sparse Matrices via Generalized Momentum Method. SMC 2018: 3051-3056 - 2017
- [j7]Xiaoyu Shi, Xin Luo, Mingsheng Shang, Liang Gu:
Long-term performance of collaborative filtering based recommenders in temporally evolving systems. Neurocomputing 267: 635-643 (2017) - [j6]Jia Chen, Xin Luo, Ye Yuan, Mingsheng Shang, Zhong Ming, Zhang Xiong:
Performance of latent factor models with extended linear biases. Knowl. Based Syst. 123: 128-136 (2017) - [j5]Xin Luo, Jianpei Sun, Zidong Wang, Shuai Li, Mingsheng Shang:
Symmetric and Nonnegative Latent Factor Models for Undirected, High-Dimensional, and Sparse Networks in Industrial Applications. IEEE Trans. Ind. Informatics 13(6): 3098-3107 (2017) - [c18]Xiao-Yu Shi, Xin Luo, Mingsheng Shang, Xin-Yi Cai:
Empirical analysis of collaborative filtering-based recommenders in temporally evolving systems. ICNSC 2017: 406-412 - [c17]Ye Yuan, Xin Luo, Mingsheng Shang, Xin-Yi Cai:
Effect of linear biases in latent factor models on high-dimensional and sparse matrices from recommender systems. ICNSC 2017: 488-494 - [c16]Xin Luo, Mingsheng Shang:
Symmetric Non-negative Latent Factor Models for Undirected Large Networks. IJCAI 2017: 2435-2442 - [c15]Yinyan Zhang, Shuai Li, Xin Luo, Mingsheng Shang:
A dynamic neural controller for adaptive optimal control of permanent magnet DC motors. IJCNN 2017: 839-844 - [c14]Long Jin, Shuai Li, Xin Luo, Mingsheng Shang:
Nonlinearly-activated noise-tolerant zeroing neural network for distributed motion planning of multiple robot arms. IJCNN 2017: 4165-4170 - [c13]Li-Yuan Xue, Rong-Qiang Zeng, Wei An, Qing-Xian Wang, Mingsheng Shang:
Experiments on Neighborhood Combination Strategies for Bi-objective Unconstrained Binary Quadratic Programming Problem. PAAP 2017: 444-453 - 2016
- [j4]Xin Luo, Mengchu Zhou, Mingsheng Shang, Shuai Li, Yunni Xia:
A Novel Approach to Extracting Non-Negative Latent Factors From Non-Negative Big Sparse Matrices. IEEE Access 4: 2649-2655 (2016) - [c12]Chao Huo, Rong-Qiang Zeng, Yang Wang, Mingsheng Shang:
A Multi-parent Crossover Based Genetic Algorithm for Bi-Objective Unconstrained Binary Quadratic Programming Problem. BIC-TA (2) 2016: 10-19 - [c11]Khushnood Abbas, Xin Luo, Mingsheng Shang:
Discovering Items with Potential Popularity on Social Media. DASC/PiCom/DataCom/CyberSciTech 2016: 459-466 - [c10]Xin Luo, Mingsheng Shang, Shuai Li:
Efficient Extraction of Non-negative Latent Factors from High-Dimensional and Sparse Matrices in Industrial Applications. ICDM 2016: 311-319 - [c9]Li-Yuan Xue, Rong-Qiang Zeng, Yang Wang, Mingsheng Shang:
Solving Bi-objective Unconstrained Binary Quadratic Programming Problem with Multi-objective Backbone Guided Search Algorithm. ICIC (2) 2016: 745-753 - [c8]Lei Song, Rong-Qiang Zeng, Yang Wang, Mingsheng Shang:
Solving bi-objective unconstrained binary quadratic programming problem with multi-objective path relinking algorithm. ICNC-FSKD 2016: 289-293 - [c7]Chao Huo, Rong-Qiang Zeng, Yang Wang, Mingsheng Shang:
An Effective Genetic Algorithm with Uniform Crossover for Bi-objective Unconstrained Binary Quadratic Programming Problem. IDEAL 2016: 58-67 - [i13]Khushnood Abbas, Mingsheng Shang, Xin Luo:
Discovering items with potential popularity on social media. CoRR abs/1604.01131 (2016) - [i12]Khushnood Abbas, Mingsheng Shang, Shi-Min Cai, Xiaoyu Shi:
Identifying emerging influential Nodes in evolving networks: Exploiting strength of weak nodes. CoRR abs/1609.01357 (2016) - 2015
- [j3]Xiuqin Zhong, Hongguang Fu, Huadong Xia, Leina Yang, Mingsheng Shang:
A hybrid cognitive assessment based on ontology knowledge map and skills. Knowl. Based Syst. 73: 52-60 (2015) - [i11]Jian Gao, Yu-Wei Dong, Mingsheng Shang, Shi-Min Cai, Tao Zhou:
Group-based ranking method for online rating systems with spamming attacks. CoRR abs/1501.00677 (2015) - [i10]Lin-Feng Zhong, Jian-Guo Liu, Ming-Sheng Shang:
Iterative resource allocation based on propagation feature of node for identifying the influential nodes. CoRR abs/1505.03214 (2015) - [i9]Yao-Dong Zhao, Shi-Min Cai, Ming Tang, Mingsheng Shang:
A Fast Recommendation Algorithm for Social Tagging Systems : A Delicious Case. CoRR abs/1512.08325 (2015) - 2014
- [j2]Yuan Guan, Shimin Cai, Mingsheng Shang:
Recommendation algorithm based on item quality and user rating preferences. Frontiers Comput. Sci. 8(2): 289-297 (2014) - [c6]Rong-Qiang Zeng, Ming-Sheng Shang:
Solving Three-Objective Flow Shop Problem with Fast Hypervolume-Based Local Search Algorithm. ICIC (2) 2014: 11-25 - [c5]Rong-Qiang Zeng, Ming-Sheng Shang:
Solving bi-objective flow shop problem with multi-objective path relinking algorithm. ICNC 2014: 343-348 - [i8]Wei Zeng, An Zeng, Hao Liu, Ming-Sheng Shang, Tao Zhou:
Uncovering the information core in recommender systems. CoRR abs/1402.6132 (2014) - 2013
- [i7]Qian-Ming Zhang, An Zeng, Ming-Sheng Shang:
Extracting the information backbone in online system. CoRR abs/1303.6369 (2013) - [i6]Wei Zeng, An Zeng, Ming-Sheng Shang, Yi-Cheng Zhang:
Membership in social networks and the application in information filtering. CoRR abs/1308.3059 (2013) - [i5]Wei Zeng, An Zeng, Ming-Sheng Shang, Yi-Cheng Zhang:
Information filtering in sparse online systems: recommendation via semi-local diffusion. CoRR abs/1308.3060 (2013) - 2012
- [c4]Sheng Huang, Mingsheng Shang, Shimin Cai:
A Hybrid Decision Approach to Detect Profile Injection Attacks in Collaborative Recommender Systems. ISMIS 2012: 377-386 - [i4]Kai Gong, Ming Tang, Hui Yang, Mingsheng Shang:
Variability of Contact Process in Complex Networks. CoRR abs/1204.0650 (2012) - 2010
- [j1]Duanbing Chen, Jingfa Liu, Yan Fu, Mingsheng Shang:
An efficient heuristic algorithm for arbitrary shaped rectilinear block packing problem. Comput. Oper. Res. 37(6): 1068-1074 (2010) - [c3]Yong Chen, Mingsheng Shang:
An Evaluation of Structure Based Similarity Indexes for Collaborative Filtering. WKDD 2010: 474-477 - [c2]Zhi-Dan Zhao, Mingsheng Shang:
User-Based Collaborative-Filtering Recommendation Algorithms on Hadoop. WKDD 2010: 478-481
2000 – 2009
- 2009
- [c1]Jie Liu, Mingsheng Shang, Duanbing Chen:
Personal Recommendation Based on Weighted Bipartite Networks. FSKD (5) 2009: 134-137 - [i3]Ming-Sheng Shang, Ci-Hang Jin, Tao Zhou, Yi-Cheng Zhang:
Collaborative filtering based on multi-channel diffusion. CoRR abs/0906.1148 (2009) - [i2]Ming-Sheng Shang, Zi-Ke Zhang, Tao Zhou, Yi-Cheng Zhang:
Collaborative filtering with diffusion-based similarity on tripartite graphs. CoRR abs/0906.5017 (2009) - [i1]Ming-Sheng Shang, Linyuan Lu, Yi-Cheng Zhang, Tao Zhou:
Empirical analysis of web-based user-object bipartite networks. CoRR abs/0909.4938 (2009)
Coauthor Index
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