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ORCIDMing Shi
This is just a disambiguation page, and is not intended to be the bibliography of an actual person. Any publication listed on this page has not been assigned to an actual author yet. If you know the true author of one of the publications listed below, you are welcome to contact us.
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2020 – today
- 2025
[j16]Zhongwei Huang
, Jianqiang Li, Jiatao Yang, Jun Wan, Jianxia Chen, Zhi Yang, Ming Shi, Ran Zhou, Haitao Gan:
Parkinson's disease classification and prediction via adaptive sparse learning from multiple modalities. Biomed. Signal Process. Control. 100: 107061 (2025)- 2024
- [j15]Qiuchen Meng, Lei Wei, Kun Ma, Ming Shi, Xinyi Lin, Joshua W. K. Ho, Yinqing Li, Xuegong Zhang:
scDecouple: decoupling cellular response from infected proportion bias in scCRISPR-seq. Briefings Bioinform. 25(2) (2024) - [j14]Zhanhong Qiu, Haitao Gan, Ming Shi, Zhongwei Huang, Zhi Yang:
Self-training with dual uncertainty for semi-supervised MRI image segmentation. Biomed. Signal Process. Control. 94: 106355 (2024) - [j13]Zhi Yang, Wenya Liu, Haitao Gan, Zhongwei Huang, Ran Zhou, Ming Shi:
Alzheimer's disease classification based on brain region-to-sample graph convolutional network. Biomed. Signal Process. Control. 96: 106589 (2024) - [j12]Ming Shi, Xiaojun Lin, Lei Jiao:
Combining Regularization With Look-Ahead for Competitive Online Convex Optimization. IEEE/ACM Trans. Netw. 32(3): 2391-2405 (2024) - 2023
- [j11]Yang Yang, Yiyang Huang, Ming Shi, Kejiang Chen, Weiming Zhang:
Invertible mask network for face privacy preservation. Inf. Sci. 629: 566-579 (2023) - [j10]Sandy Adhitia Ekahana, Genta Indra Winata, Y. Soh, Anna Tamai, Radovic Milan, Gabriel Aeppli, Ming Shi:
Transfer learning application of self-supervised learning in ARPES. Mach. Learn. Sci. Technol. 4(3): 35021 (2023) - [c16]Ming Shi, Yingbin Liang, Ness B. Shroff:
Near-Optimal Adversarial Reinforcement Learning with Switching Costs. ICLR 2023 - [c15]Ming Shi, Yingbin Liang, Ness B. Shroff:
A Near-Optimal Algorithm for Safe Reinforcement Learning Under Instantaneous Hard Constraints. ICML 2023: 31243-31268 - [c14]Jiahui Wen, Haitao Gan, Zhi Yang, Ming Shi, Ji Wang:
MView-DTI: A Multi-view Feature Fusion-Based Approach for Drug-Target Protein Interaction Prediction. ICONIP (10) 2023: 400-411 - [c13]Wenjie Yu, Weiyan Gan, Furong Wang, Zhi Yang, Ming Shi, Ran Zhou:
Semi-Supervised Carotid Plaque Image Classification Using Feature Correction and Pseudo-Label Balance Correction. SMC 2023: 672-677 - [i7]Ming Shi, Yingbin Liang, Ness B. Shroff:
Near-Optimal Adversarial Reinforcement Learning with Switching Costs. CoRR abs/2302.04374 (2023) - [i6]Ming Shi, Yingbin Liang, Ness B. Shroff:
A Near-Optimal Algorithm for Safe Reinforcement Learning Under Instantaneous Hard Constraints. CoRR abs/2302.04375 (2023) - [i5]Zhi Yang, Kang Li, Haitao Gan, Zhongwei Huang, Ming Shi:
HD-GCN: A Hybrid Diffusion Graph Convolutional Network. CoRR abs/2303.17966 (2023) - [i4]Zhanhong Qiu, Haitao Gan, Ming Shi, Zhongwei Huang, Zhi Yang:
Self-training with dual uncertainty for semi-supervised medical image segmentation. CoRR abs/2304.04441 (2023) - [i3]Ming Shi, Yingbin Liang, Ness B. Shroff:
Theoretical Hardness and Tractability of POMDPs in RL with Partial Hindsight State Information. CoRR abs/2306.08762 (2023) - 2022
- [j9]Ming Shi, Yang Yang, Jian Meng, Weiming Zhang:
Reversible data hiding with enhancing contrast and preserving brightness in medical image. J. Inf. Secur. Appl. 70: 103324 (2022) - [j8]Boyang Ti, Yongsheng Gao, Ming Shi, Jie Zhao:
Generalization of orientation trajectories and force-torque profiles for learning human assembly skill. Robotics Comput. Integr. Manuf. 76: 102325 (2022) - [c12]Sen Lin, Ming Shi, Anish Arora, Raef Bassily, Elisa Bertino, Constantine Caramanis, Kaushik R. Chowdhury, Eylem Ekici, Atilla Eryilmaz, Stratis Ioannidis, Nan Jiang, Gauri Joshi, Jim Kurose, Yingbin Liang, Zhiqiang Lin, Jia Liu, Mingyan Liu, Tommaso Melodia, Aryan Mokhtari, Rob Nowak, Sewoong Oh, Srini Parthasarathy, Chunyi Peng, Hulya Seferoglu, Ness B. Shroff, Sanjay Shakkottai, Kannan Srinivasan, Ameet Talwalkar, Aylin Yener, Lei Ying:
Leveraging Synergies Between AI and Networking to Build Next Generation Edge Networks. CIC 2022: 16-25 - [c11]Ming Shi, Jing Zhao:
A Knowledge Graph Link Prediction Model with Combined 1D and 2D Convolutional Embeddings. DSAA 2022: 1-2 - [c10]Donglin Wu, Jing Zhao, Ming Li, Ming Shi:
A Knowledge Representation Method for Multiple Pattern Embeddings Based on Entity-Relation Mapping Matrix. IJCNN 2022: 1-8 - [c9]Ming Shi, Xiaojun Lin, Lei Jiao:
Power-of-2-arms for bandit learning with switching costs. MobiHoc 2022: 131-140 - [c8]Wenya Liu, Zhi Yang, Haitao Gan, Zhongwei Huang, Ran Zhou, Ming Shi:
Hierarchical Pooling Graph Convolutional Neural Network for Alzheimer's Disease Diagnosis. PRICAI (1) 2022: 426-437 - [c7]Hongmin Zhang, Ming Shi, Zhongwei Huang, Zhi Yang, Ran Zhou, Haitao Gan:
VaeSSC: Enhanced GRN Inference with Structural Similarity Constrained Beta-VAE. PRICAI (1) 2022: 451-463 - [i2]Yang Yang, Yiyang Huang, Ming Shi, Kejiang Chen, Weiming Zhang, Nenghai Yu:
Invertible Mask Network for Face Privacy-Preserving. CoRR abs/2204.08895 (2022) - [i1]Sandy Adhitia Ekahana, Genta Indra Winata, Y. Soh, Gabriel Aeppli, Radovic Milan, Ming Shi:
Transfer Learning Application of Self-supervised Learning in ARPES. CoRR abs/2208.10893 (2022) - 2021
- [j7]Haiyang Peng, Dingding Yang, Tianzhen Wang, Shreya Pandey, Lisu Chen, Ming Shi, Demba Diallo:
An adaptive coarse-fine semantic segmentation method for the attachment recognition on marine current turbines. Comput. Electr. Eng. 93: 107182 (2021) - [j6]Zhipeng Li, Xiaolan Li, Ming Shi, Wenli Song, Guowei Zhao, Ruizhu Yang, Shangbin Li:
Tracking algorithm of snowboard target in intelligent system. J. Intell. Fuzzy Syst. 40(2): 3117-3125 (2021) - [j5]Ming Shi, Xiaojun Lin, Sonia Fahmy:
Competitive Online Convex Optimization With Switching Costs and Ramp Constraints. IEEE/ACM Trans. Netw. 29(2): 876-889 (2021) - [c6]Ming Shi, Yongsheng Gao, Boyang Ti, Jie Zhao:
Obstacle Avoidance Methods Based on Geometric Information Under the DMPs Framework. ICIRA (2) 2021: 58-69 - [c5]Ming Shi, Xiaojun Lin, Lei Jiao:
Combining Regularization with Look-Ahead for Competitive Online Convex Optimization. INFOCOM 2021: 1-10
2010 – 2019
- 2019
- [j4]Ming Shi, Dan Li, Jian Qiu Zhang:
Matrix Polynomial Predictive Model: A New Approach to Accelerating the PARAFAC Decomposition. IEEE Access 7: 91872-91884 (2019) - [j3]Ming Shi, Xiaojun Lin, Lei Jiao:
On the Value of Look-Ahead in Competitive Online Convex Optimization. Proc. ACM Meas. Anal. Comput. Syst. 3(2): 22:1-22:42 (2019) - 2018
- [j2]Ming Shi, Dan Li, Jian Qiu Zhang:
An Alternating Bayesian Approach to PARAFAC Decomposition of Tensors. IEEE Access 6: 36487-36499 (2018) - [j1]Dan Li, Ming Shi, Feng Xu, Chengcheng Liu, Jianqiu Zhang, Dean Ta:
A New Approach to Guided Wave Ray Tomography for Temperature-Robust Damage Detection Using Piezoelectric Sensors. Sensors 18(10): 3518 (2018) - [c4]Ming Shi, Xiaojun Lin, Sonia Fahmy, Dong-Hoon Shin:
Competitive Online Convex Optimization with Switching Costs and Ramp Constraints. INFOCOM 2018: 1835-1843 - 2017
- [c3]Ming Shi, JianQiu Zhang, Bo Hu, Bin Wang, Qiyong Lu:
Convergence acceleration of alternating least squares with a matrix polynomial predictive model for PARAFAC decomposition of a tensor. EUSIPCO 2017: 1115-1119 - 2016
- [c2]Ming Shi, Yanwen Chong, Shao-Ming Pan:
Performance and Improvement of Tree-Based Methods for Gene Regulatory Network Reconstruction. ICIC (1) 2016: 205-213 - 2012
- [c1]Fuluo Wang, Yourui Huang, Ming Shi, Shanshan Wu:
Membrane Computing Optimization Method Based on Catalytic Factor. BICS 2012: 129-137
Coauthor Index
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