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ORCIDMin Zhou 0006
Person information
- affiliation: Huawei Technologies Co. Ltd, Shenzhen, China
- affiliation (PhD 2016): National University of Singapore, ndustrial and Systems Engineering Department
Other persons with the same name
- Min Zhou — disambiguation page
- Min Zhou 0001
![[0000-0002-4679-0488]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0002-4679-0488")
— Tsinghua University, School of Software, Beijing, China - Min Zhou 0002 — Queen Mary University of London, UK
- Min Zhou 0003 — Beijing Jiaotong University, State Key Laboratory of Rail Traffic Control and Safety, China
- Min Zhou 0004 — East China University of Science and Technology, Key Laboratory of Smart Manufacturing in Energy Chemical Process, Shanghai, China (and 1 more)
- Min Zhou 0005 — China Agricultural University, College of Engineering, Beijing, China
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Journal Articles
- 2025
[j10]Shengzhong Zhang, Yimin Zhang, Bisheng Li, Wenjie Yang, Min Zhou, Zengfeng Huang:
Graph Batch Coarsening framework for scalable graph neural networks. Neural Networks 183: 106931 (2025)- 2024
- [j9]Chenwang Wu, Defu Lian, Yong Ge, Min Zhou, Enhong Chen, Dacheng Tao:
Boosting Factorization Machines via Saliency-Guided Mixup. IEEE Trans. Pattern Anal. Mach. Intell. 46(6): 4443-4459 (2024) - [j8]Chenwang Wu, Defu Lian, Yong Ge, Min Zhou, Enhong Chen:
Attacking Social Media via Behavior Poisoning. ACM Trans. Knowl. Discov. Data 18(7): 169 (2024) - 2023
- [j7]Xuemeng Song, Chun Wang, Changchang Sun, Shanshan Feng, Min Zhou, Liqiang Nie:
MM-FRec: Multi-Modal Enhanced Fashion Item Recommendation. IEEE Trans. Knowl. Data Eng. 35(10): 10072-10084 (2023) - [j6]Menglin Yang, Min Zhou, Hui Xiong, Irwin King:
Hyperbolic Temporal Network Embedding. IEEE Trans. Knowl. Data Eng. 35(11): 11489-11502 (2023) - 2022
- [j5]Jiahong Liu, Philippe Fournier-Viger, Min Zhou, Ganghuan He, Mourad Nouioua:
CSPM: Discovering compressing stars in attributed graphs. Inf. Sci. 611: 126-158 (2022) - 2020
- [j4]Philippe Fournier-Viger, Ganghuan He, Chao Cheng, Jiaxuan Li, Min Zhou, Jerry Chun-Wei Lin, Unil Yun:
A survey of pattern mining in dynamic graphs. WIREs Data Mining Knowl. Discov. 10(6) (2020) - 2017
- [j3]Jinwen Hu, Min Zhou, Xiang Li, Zhao Xu:
Online model regression for nonlinear time-varying manufacturing systems. Autom. 78: 163-173 (2017) - 2016
- [j2]Min Zhou, T. N. Goh:
Effects of Model Accuracy on Residual Control Charts. Qual. Reliab. Eng. Int. 32(5): 1785-1794 (2016) - [j1]Min Zhou, T. N. Goh:
Iterative Designed Experiment Analysis (IDEA). Qual. Reliab. Eng. Int. 32(8): 2977-2986 (2016)
Conference and Workshop Papers
- 2025
- [c22]Hongliang Qiao, Shanshan Feng, Min Zhou, Wentao Li, Fan Li:
Hyperbolic Multi-semantic Transition for Next POI Recommendation. WWW (Companion Volume) 2025: 1830-1837 - [c21]Min Zhou, Hongyi Xie, Qiao Yu, Jialiang Yu, Zhenli Sheng:
SmartMem: Memory Failure Prediction Challenge at WWW 2025. WWW (Companion Volume) 2025: 3003-3007 - 2024
- [c20]Tianmeng Yang, Jiahao Meng, Min Zhou, Yaming Yang, Yujing Wang, Xiangtai Li, Yunhai Tong:
You Can't Ignore Either: Unifying Structure and Feature Denoising for Robust Graph Learning. CIKM 2024: 4178-4182 - [c19]Kaidi Li, Tianmeng Yang, Min Zhou, Jiahao Meng, Shendi Wang, Yihui Wu, Boshuai Tan, Hu Song, Lujia Pan, Fan Yu, Zhenli Sheng, Yunhai Tong:
SEFraud: Graph-based Self-Explainable Fraud Detection via Interpretative Mask Learning. KDD 2024: 5329-5338 - [c18]Jiashu Han, Shanshan Feng, Min Zhou, Xinyu Zhang, Yew Soon Ong, Xutao Li:
Diffusion Model in Normal Gathering Latent Space for Time Series Anomaly Detection. ECML/PKDD (3) 2024: 284-300 - 2023
- [c17]Junfeng Liu, Min Zhou, Shuai Ma, Lujia Pan:
MATA*: Combining Learnable Node Matching with A* Algorithm for Approximate Graph Edit Distance Computation. CIKM 2023: 1503-1512 - [c16]Tianmeng Yang, Min Zhou, Yujing Wang, Zhengjie Lin, Lujia Pan, Bin Cui, Yunhai Tong:
Mitigating Semantic Confusion from Hostile Neighborhood for Graph Active Learning. CIKM 2023: 4380-4384 - [c15]Junfeng Liu, Liwei Ni, Xingquan Li, Min Zhou, Lei Chen, Xing Li, Qinghua Zhao, Shuai Ma:
AiMap: Learning to Improve Technology Mapping for ASICs via Delay Prediction. ICCD 2023: 344-347 - [c14]Menglin Yang, Min Zhou, Rex Ying, Yankai Chen, Irwin King:
Hyperbolic Representation Learning: Revisiting and Advancing. ICML 2023: 39639-39659 - [c13]Menglin Yang, Min Zhou, Lujia Pan, Irwin King:
κHGCN: Tree-likeness Modeling via Continuous and Discrete Curvature Learning. KDD 2023: 2965-2977 - [c12]Min Zhou, Menglin Yang, Bo Xiong, Hui Xiong, Irwin King:
Hyperbolic Graph Neural Networks: A Tutorial on Methods and Applications. KDD 2023: 5843-5844 - 2022
- [c11]Jiahong Liu, Min Zhou, Philippe Fournier-Viger, Menglin Yang, Lujia Pan, Mourad Nouioua:
Discovering Representative Attribute-stars via Minimum Description Length. ICDE 2022: 68-80 - [c10]Menglin Yang, Zhihao Li, Min Zhou, Jiahong Liu, Irwin King:
HICF: Hyperbolic Informative Collaborative Filtering. KDD 2022: 2212-2221 - [c9]Zhihao Zhu, Chenwang Wu, Min Zhou, Hao Liao, Defu Lian, Enhong Chen:
Resisting Graph Adversarial Attack via Cooperative Homophilous Augmentation. ECML/PKDD (3) 2022: 251-268 - [c8]Bisheng Li, Min Zhou, Shengzhong Zhang, Menglin Yang, Defu Lian, Zengfeng Huang:
BSAL: A Framework of Bi-component Structure and Attribute Learning for Link Prediction. SIGIR 2022: 2053-2058 - [c7]Menglin Yang, Min Zhou, Jiahong Liu, Defu Lian, Irwin King:
HRCF: Enhancing Collaborative Filtering via Hyperbolic Geometric Regularization. WWW 2022: 2462-2471 - 2021
- [c6]Zengfeng Huang, Shengzhong Zhang, Chong Xi, Tang Liu, Min Zhou:
Scaling Up Graph Neural Networks Via Graph Coarsening. KDD 2021: 675-684 - [c5]Menglin Yang, Min Zhou, Marcus Kalander, Zengfeng Huang, Irwin King:
Discrete-time Temporal Network Embedding via Implicit Hierarchical Learning in Hyperbolic Space. KDD 2021: 1975-1985 - [c4]Moritz Neun, Christian Eichenberger, Henry Martin, Markus Spanring, Rahul Siripurapu, Daniel Springer, Leyan Deng, Chenwang Wu, Defu Lian, Min Zhou, Martin Lumiste, Andrei Ilie, Xinhua Wu, Cheng Lyu, Qing-Long Lu, Vishal Mahajan, Yichao Lu, Jiezhang Li, Junjun Li, Yue-Jiao Gong, Florian Grötschla, Joël Mathys, Ye Wei, He Haitao, Hui Fang, Kevin Malm, Fei Tang, Michael Kopp, David P. Kreil, Sepp Hochreiter:
Traffic4cast at NeurIPS 2022 – Predict Dynamics along Graph Edges from Sparse Node Data: Whole City Traffic and ETA from Stationary Vehicle Detectors. NeurIPS (Competition and Demos) 2021: 251-278 - 2020
- [c3]Keli Zhang, Marcus Kalander, Min Zhou, Xi Zhang, Junjian Ye:
An Influence-Based Approach for Root Cause Alarm Discovery in Telecom Networks. ICSOC Workshops 2020: 124-136 - [c2]Philippe Fournier-Viger, Ganghuan He, Min Zhou, Mourad Nouioua, Jiahong Liu:
Discovering Alarm Correlation Rules for Network Fault Management. ICSOC Workshops 2020: 228-239 - 2016
- [c1]Min Zhou, Zhao-Qin Guo, Xiang Li:
Design of model predictive control for time-varying nonlinear system based on gaussian process regression modeling. ETFA 2016: 1-6
Editorship
- 2021
- [e2]Michael Kamp, Irena Koprinska, Adrien Bibal, Tassadit Bouadi, Benoît Frénay, Luis Galárraga, José Oramas, Linara Adilova, Yamuna Krishnamurthy, Bo Kang, Christine Largeron, Jefrey Lijffijt, Tiphaine Viard, Pascal Welke, Massimiliano Ruocco, Erlend Aune, Claudio Gallicchio, Gregor Schiele, Franz Pernkopf, Michaela Blott, Holger Fröning, Günther Schindler, Riccardo Guidotti, Anna Monreale, Salvatore Rinzivillo, Przemyslaw Biecek, Eirini Ntoutsi, Mykola Pechenizkiy, Bodo Rosenhahn, Christopher L. Buckley, Daniela Cialfi, Pablo Lanillos, Maxwell Ramstead, Tim Verbelen, Pedro M. Ferreira, Giuseppina Andresini, Donato Malerba, Ibéria Medeiros, Philippe Fournier-Viger, M. Saqib Nawaz, Sebastián Ventura, Meng Sun, Min Zhou, Valerio Bitetta, Ilaria Bordino, Andrea Ferretti, Francesco Gullo, Giovanni Ponti, Lorenzo Severini, Rita P. Ribeiro, João Gama, Ricard Gavaldà, Lee Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Damian Roqueiro, Diego Saldana Miranda, Konstantinos Sechidis, Guilherme Graça:
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021, Proceedings, Part I. Communications in Computer and Information Science 1524, Springer 2021, ISBN 978-3-030-93735-5 [contents] - [e1]Michael Kamp, Irena Koprinska, Adrien Bibal, Tassadit Bouadi, Benoît Frénay, Luis Galárraga, José Oramas, Linara Adilova, Yamuna Krishnamurthy, Bo Kang, Christine Largeron, Jefrey Lijffijt, Tiphaine Viard, Pascal Welke, Massimiliano Ruocco, Erlend Aune, Claudio Gallicchio, Gregor Schiele, Franz Pernkopf, Michaela Blott, Holger Fröning, Günther Schindler, Riccardo Guidotti, Anna Monreale, Salvatore Rinzivillo, Przemyslaw Biecek, Eirini Ntoutsi, Mykola Pechenizkiy, Bodo Rosenhahn, Christopher L. Buckley, Daniela Cialfi, Pablo Lanillos, Maxwell Ramstead, Tim Verbelen, Pedro M. Ferreira, Giuseppina Andresini, Donato Malerba, Ibéria Medeiros, Philippe Fournier-Viger, M. Saqib Nawaz, Sebastián Ventura, Meng Sun, Min Zhou, Valerio Bitetta, Ilaria Bordino, Andrea Ferretti, Francesco Gullo, Giovanni Ponti, Lorenzo Severini, Rita P. Ribeiro, João Gama, Ricard Gavaldà, Lee Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Damian Roqueiro, Diego Saldana Miranda, Konstantinos Sechidis, Guilherme Graça:
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021, Proceedings, Part II. Communications in Computer and Information Science 1525, Springer 2021, ISBN 978-3-030-93732-4 [contents]
Informal and Other Publications
- 2025
- [i25]Menglin Yang, Jialin Chen, Yifei Zhang, Jiahong Liu, Jiasheng Zhang, Qiyao Ma, Harshit Verma, Qianru Zhang, Min Zhou, Irwin King, Rex Ying:
Low-Rank Adaptation for Foundation Models: A Comprehensive Review. CoRR abs/2501.00365 (2025) - 2024
- [i24]Kaidi Li, Tianmeng Yang, Min Zhou, Jiahao Meng, Shendi Wang, Yihui Wu, Boshuai Tan, Hu Song, Lujia Pan, Fan Yu, Zhenli Sheng, Yunhai Tong:
SEFraud: Graph-based Self-Explainable Fraud Detection via Interpretative Mask Learning. CoRR abs/2406.11389 (2024) - [i23]Yu Huang, Min Zhou, Menglin Yang, Zhen Wang, Muhan Zhang, Jie Wang, Hong Xie, Hao Wang, Defu Lian, Enhong Chen:
Foundations and Frontiers of Graph Learning Theory. CoRR abs/2407.03125 (2024) - [i22]Tianmeng Yang, Jiahao Meng, Min Zhou, Yaming Yang, Yujing Wang, Xiangtai Li, Yunhai Tong:
You Can't Ignore Either: Unifying Structure and Feature Denoising for Robust Graph Learning. CoRR abs/2408.00700 (2024) - 2023
- [i21]Moritz Neun, Christian Eichenberger, Henry Martin, Markus Spanring, Rahul Siripurapu, Daniel Springer, Leyan Deng, Chenwang Wu, Defu Lian, Min Zhou, Martin Lumiste, Andrei Ilie, Xinhua Wu, Cheng Lyu, Qing-Long Lu, Vishal Mahajan, Yichao Lu, Jiezhang Li, Junjun Li, Yue-Jiao Gong, Florian Grötschla, Joël Mathys, Ye Wei, He Haitao, Hui Fang, Kevin Malm, Fei Tang, Michael Kopp, David P. Kreil, Sepp Hochreiter:
Traffic4cast at NeurIPS 2022 - Predict Dynamics along Graph Edges from Sparse Node Data: Whole City Traffic and ETA from Stationary Vehicle Detectors. CoRR abs/2303.07758 (2023) - [i20]Liang Yan, Shengzhong Zhang, Bisheng Li, Min Zhou, Zengfeng Huang:
UNREAL: Unlabeled Nodes Retrieval and Labeling for Heavily-imbalanced Node Classification. CoRR abs/2303.10371 (2023) - [i19]Menglin Yang, Min Zhou, Rex Ying, Yankai Chen, Irwin King:
Hyperbolic Representation Learning: Revisiting and Advancing. CoRR abs/2306.09118 (2023) - [i18]Tianmeng Yang, Min Zhou, Yujing Wang, Zhengjie Lin, Lujia Pan, Bin Cui, Yunhai Tong:
Mitigating Semantic Confusion from Hostile Neighborhood for Graph Active Learning. CoRR abs/2308.08823 (2023) - [i17]Junfeng Liu, Min Zhou, Shuai Ma, Lujia Pan:
MATA*: Combining Learnable Node Matching with A* Algorithm for Approximate Graph Edit Distance Computation. CoRR abs/2311.02356 (2023) - 2022
- [i16]Jiahong Liu, Menglin Yang, Min Zhou, Shanshan Feng, Philippe Fournier-Viger:
Enhancing Hyperbolic Graph Embeddings via Contrastive Learning. CoRR abs/2201.08554 (2022) - [i15]Menglin Yang, Min Zhou, Zhihao Li, Jiahong Liu, Lujia Pan, Hui Xiong, Irwin King:
Hyperbolic Graph Neural Networks: A Review of Methods and Applications. CoRR abs/2202.13852 (2022) - [i14]Min Zhou, Bisheng Li, Menglin Yang, Lujia Pan:
TeleGraph: A Benchmark Dataset for Hierarchical Link Prediction. CoRR abs/2204.07703 (2022) - [i13]Menglin Yang, Min Zhou, Jiahong Liu, Defu Lian, Irwin King:
HRCF: Enhancing Collaborative Filtering via Hyperbolic Geometric Regularization. CoRR abs/2204.08176 (2022) - [i12]Bisheng Li, Min Zhou, Shengzhong Zhang, Menglin Yang, Defu Lian, Zengfeng Huang:
BSAL: A Framework of Bi-component Structure and Attribute Learning for Link Prediction. CoRR abs/2204.09508 (2022) - [i11]Jiahong Liu, Min Zhou, Philippe Fournier-Viger, Menglin Yang, Lujia Pan, Mourad Nouioua:
Discovering Representative Attribute-stars via Minimum Description Length. CoRR abs/2204.12704 (2022) - [i10]Chenwang Wu, Defu Lian, Yong Ge, Min Zhou, Enhong Chen, Dacheng Tao:
Boosting Factorization Machines via Saliency-Guided Mixup. CoRR abs/2206.08661 (2022) - [i9]Menglin Yang, Zhihao Li, Min Zhou, Jiahong Liu, Irwin King:
HICF: Hyperbolic Informative Collaborative Filtering. CoRR abs/2207.09051 (2022) - [i8]Leyan Deng, Chenwang Wu, Defu Lian, Min Zhou:
Transposed Variational Auto-encoder with Intrinsic Feature Learning for Traffic Forecasting. CoRR abs/2211.00641 (2022) - [i7]Min Zhou, Menglin Yang, Lujia Pan, Irwin King:
Hyperbolic Graph Representation Learning: A Tutorial. CoRR abs/2211.04050 (2022) - [i6]Zhihao Zhu, Chenwang Wu, Min Zhou, Hao Liao, Defu Lian, Enhong Chen:
Resisting Graph Adversarial Attack via Cooperative Homophilous Augmentation. CoRR abs/2211.08068 (2022) - [i5]Menglin Yang, Min Zhou, Lujia Pan, Irwin King:
Hyperbolic Curvature Graph Neural Network. CoRR abs/2212.01793 (2022) - 2021
- [i4]Keli Zhang, Marcus Kalander, Min Zhou, Xi Zhang, Junjian Ye:
An Influence-based Approach for Root Cause Alarm Discovery in Telecom Networks. CoRR abs/2105.03092 (2021) - [i3]Zengfeng Huang, Shengzhong Zhang, Chong Xi, Tang Liu, Min Zhou:
Scaling Up Graph Neural Networks Via Graph Coarsening. CoRR abs/2106.05150 (2021) - [i2]Menglin Yang, Min Zhou, Marcus Kalander, Zengfeng Huang, Irwin King:
Discrete-time Temporal Network Embedding via Implicit Hierarchical Learning in Hyperbolic Space. CoRR abs/2107.03767 (2021) - 2020
- [i1]Marcus Kalander, Min Zhou, Chengzhi Zhang, Hanling Yi, Lujia Pan:
Spatio-Temporal Hybrid Graph Convolutional Network for Traffic Forecasting in Telecommunication Networks. CoRR abs/2009.09849 (2020)
Coauthor Index
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