Design of model predictive control for time-varying nonlinear system based on gaussian process regression modeling. - Min Zhou 006; Zhao-Qin Guo; Xiang Li 040 (ETFA, 2016)

Effects of Model Accuracy on Residual Control Charts. - Min Zhou 006; T. N. Goh (Qual. Reliab. Eng. Int., 2016)

Iterative Designed Experiment Analysis (IDEA). - Min Zhou 006; T. N. Goh (Qual. Reliab. Eng. Int., 2016)

Online model regression for nonlinear time-varying manufacturing systems. - Jinwen Hu; Min Zhou 006; Xiang Li 040; Zhao Xu (Autom., 2017)

Discovering Alarm Correlation Rules for Network Fault Management. - Philippe Fournier-Viger; Ganghuan He; Min Zhou 006; Mourad Nouioua; Jiahong Liu 001 (ICSOC Workshops, 2020)

An Influence-Based Approach for Root Cause Alarm Discovery in Telecom Networks. - Keli Zhang; Marcus Kalander; Min Zhou 006; Xi Zhang; Junjian Ye (ICSOC Workshops, 2020)

Spatio-Temporal Hybrid Graph Convolutional Network for Traffic Forecasting in Telecommunication Networks. - Marcus Kalander; Min Zhou 006; Chengzhi Zhang; Hanling Yi; Lujia Pan (CoRR, 2020)

A survey of pattern mining in dynamic graphs. - Philippe Fournier-Viger; Ganghuan He; Chao Cheng; Jiaxuan Li; Min Zhou 006; Jerry Chun-Wei Lin; Unil Yun (WIREs Data Mining Knowl. Discov., 2020)

Discrete-time Temporal Network Embedding via Implicit Hierarchical Learning in Hyperbolic Space. - Menglin Yang 001; Min Zhou 006; Marcus Kalander; Zengfeng Huang; Irwin King (KDD, 2021)

Scaling Up Graph Neural Networks Via Graph Coarsening. - Zengfeng Huang; Shengzhong Zhang; Chong Xi; Tang Liu; Min Zhou 006 (KDD, 2021)

Traffic4cast at NeurIPS 2022 – Predict Dynamics along Graph Edges from Sparse Node Data: Whole City Traffic and ETA from Stationary Vehicle Detectors. - Moritz Neun; Christian Eichenberger; Henry Martin; Markus Spanring; Rahul Siripurapu; Daniel Springer; Leyan Deng; Chenwang Wu; Defu Lian; Min Zhou 006; Martin Lumiste; Andrei Ilie; et al. (NeurIPS (Competition and Demos), 2021)

Discovering Representative Attribute-stars via Minimum Description Length. - Jiahong Liu 001; Min Zhou 006; Philippe Fournier-Viger; Menglin Yang 001; Lujia Pan; Mourad Nouioua (ICDE, 2022)

HICF: Hyperbolic Informative Collaborative Filtering. - Menglin Yang 001; Zhihao Li 004; Min Zhou 006; Jiahong Liu 001; Irwin King (KDD, 2022)

Resisting Graph Adversarial Attack via Cooperative Homophilous Augmentation. - Zhihao Zhu 002; Chenwang Wu; Min Zhou 006; Hao Liao; Defu Lian; Enhong Chen (ECML/PKDD (3), 2022)

BSAL: A Framework of Bi-component Structure and Attribute Learning for Link Prediction. - Bisheng Li; Min Zhou 006; Shengzhong Zhang; Menglin Yang 001; Defu Lian; Zengfeng Huang (SIGIR, 2022)

HRCF: Enhancing Collaborative Filtering via Hyperbolic Geometric Regularization. - Menglin Yang 001; Min Zhou 006; Jiahong Liu 001; Defu Lian; Irwin King (WWW, 2022)

Enhancing Hyperbolic Graph Embeddings via Contrastive Learning. - Jiahong Liu 001; Menglin Yang 001; Min Zhou 006; Shanshan Feng 001; Philippe Fournier-Viger (CoRR, 2022)

Hyperbolic Graph Neural Networks: A Review of Methods and Applications. - Menglin Yang 001; Min Zhou 006; Zhihao Li 004; Jiahong Liu 001; Lujia Pan; Hui Xiong 001; Irwin King (CoRR, 2022)

TeleGraph: A Benchmark Dataset for Hierarchical Link Prediction. - Min Zhou 006; Bisheng Li; Menglin Yang 001; Lujia Pan (CoRR, 2022)

Transposed Variational Auto-encoder with Intrinsic Feature Learning for Traffic Forecasting. - Leyan Deng; Chenwang Wu; Defu Lian; Min Zhou 006 (CoRR, 2022)

Hyperbolic Graph Representation Learning: A Tutorial. - Min Zhou 006; Menglin Yang 001; Lujia Pan; Irwin King (CoRR, 2022)

Hyperbolic Curvature Graph Neural Network. - Menglin Yang 001; Min Zhou 006; Lujia Pan; Irwin King (CoRR, 2022)

CSPM: Discovering compressing stars in attributed graphs. - Jiahong Liu 001; Philippe Fournier-Viger; Min Zhou 006; Ganghuan He; Mourad Nouioua (Inf. Sci., 2022)

MATA*: Combining Learnable Node Matching with A* Algorithm for Approximate Graph Edit Distance Computation. - Junfeng Liu; Min Zhou 006; Shuai Ma 001; Lujia Pan (CIKM, 2023)

Mitigating Semantic Confusion from Hostile Neighborhood for Graph Active Learning. - Tianmeng Yang; Min Zhou 006; Yujing Wang; Zhengjie Lin; Lujia Pan; Bin Cui 001; Yunhai Tong (CIKM, 2023)

AiMap: Learning to Improve Technology Mapping for ASICs via Delay Prediction. - Junfeng Liu; Liwei Ni; Xingquan Li; Min Zhou 006; Lei Chen 031; Xing Li; Qinghua Zhao; Shuai Ma 001 (ICCD, 2023)

Hyperbolic Representation Learning: Revisiting and Advancing. - Menglin Yang 001; Min Zhou 006; Rex Ying; Yankai Chen 001; Irwin King (ICML, 2023)

κHGCN: Tree-likeness Modeling via Continuous and Discrete Curvature Learning. - Menglin Yang 001; Min Zhou 006; Lujia Pan; Irwin King (KDD, 2023)

Hyperbolic Graph Neural Networks: A Tutorial on Methods and Applications. - Min Zhou 006; Menglin Yang 001; Bo Xiong; Hui Xiong 001; Irwin King (KDD, 2023)

UNREAL: Unlabeled Nodes Retrieval and Labeling for Heavily-imbalanced Node Classification. - Liang Yan; Shengzhong Zhang; Bisheng Li; Min Zhou 006; Zengfeng Huang (CoRR, 2023)

MM-FRec: Multi-Modal Enhanced Fashion Item Recommendation. - Xuemeng Song; Chun Wang; Changchang Sun; Shanshan Feng 001; Min Zhou 006; Liqiang Nie (IEEE Trans. Knowl. Data Eng., 2023)

Hyperbolic Temporal Network Embedding. - Menglin Yang 001; Min Zhou 006; Hui Xiong 001; Irwin King (IEEE Trans. Knowl. Data Eng., 2023)

You Can't Ignore Either: Unifying Structure and Feature Denoising for Robust Graph Learning. - Tianmeng Yang; Jiahao Meng; Min Zhou 006; Yaming Yang 001; Yujing Wang; Xiangtai Li; Yunhai Tong (CIKM, 2024)

SEFraud: Graph-based Self-Explainable Fraud Detection via Interpretative Mask Learning. - Kaidi Li; Tianmeng Yang; Min Zhou 006; Jiahao Meng; Shendi Wang; Yihui Wu; Boshuai Tan; Hu Song; Lujia Pan; Fan Yu; Zhenli Sheng; Yunhai Tong (KDD, 2024)

Diffusion Model in Normal Gathering Latent Space for Time Series Anomaly Detection. - Jiashu Han; Shanshan Feng 001; Min Zhou 006; Xinyu Zhang; Yew Soon Ong; Xutao Li (ECML/PKDD (3), 2024)

Foundations and Frontiers of Graph Learning Theory. - Yu Huang; Min Zhou 006; Menglin Yang 001; Zhen Wang; Muhan Zhang; Jie Wang 005; Hong Xie 004; Hao Wang 076; Defu Lian; Enhong Chen (CoRR, 2024)

Boosting Factorization Machines via Saliency-Guided Mixup. - Chenwang Wu; Defu Lian; Yong Ge; Min Zhou 006; Enhong Chen; Dacheng Tao (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

Attacking Social Media via Behavior Poisoning. - Chenwang Wu; Defu Lian; Yong Ge; Min Zhou 006; Enhong Chen (ACM Trans. Knowl. Discov. Data, 2024)

SmartMem: Memory Failure Prediction Challenge at WWW 2025. - Min Zhou 006; Hongyi Xie; Qiao Yu; Jialiang Yu; Zhenli Sheng (WWW (Companion Volume), 2025)

Hyperbolic Multi-semantic Transition for Next POI Recommendation. - Hongliang Qiao; Shanshan Feng 001; Min Zhou 006; Wentao Li; Fan Li 015 (WWW (Companion Volume), 2025)

Graph Batch Coarsening framework for scalable graph neural networks. - Shengzhong Zhang; Yimin Zhang; Bisheng Li; Wenjie Yang 006; Min Zhou 006; Zengfeng Huang (Neural Networks, 2025)

Low-Rank Adaptation for Foundation Models: A Comprehensive Review. - Menglin Yang 001; Jialin Chen; Yifei Zhang; Jiahong Liu 001; Jiasheng Zhang; Qiyao Ma; Harshit Verma; Qianru Zhang; Min Zhou 006; Irwin King; Rex Ying (CoRR, 2025)

M2-MFP: A Multi-Scale and Multi-Level Memory Failure Prediction Framework for Reliable Cloud Infrastructure. - Hongyi Xie; Min Zhou 006; Qiao Yu; Jialiang Yu; Zhenli Sheng; Hong Xie 004; Defu Lian (CoRR, 2025)