| Enhancing State-of-the-art Classifiers with API Semantics to Detect Evolved Android Malware X Zhang, Y Zhang, M Zhong, D Ding, Y Cao, Y Zhang, M Zhang, M Yang 27th ACM Conference on Computer and Communications Security (CCS), 2020 | 157 | 2020 |
| Modeling extreme events in time series prediction D Ding, M Zhang, X Pan, M Yang, X He 25th ACM SIGKDD International Conference on Knowledge Discovery & Data …, 2019 | 133 | 2019 |
| Baydnn: Friend recommendation with bayesian personalized ranking deep neural network D Ding, M Zhang, SY Li, J Tang, X Chen, ZH Zhou 26th ACM on Conference on Information and Knowledge Management (CIKM), 2017 | 59 | 2017 |
| Geographical feature extraction for entities in location-based social networks D Ding, M Zhang, X Pan, D Wu, P Pu 2018 World Wide Web Conference (WWW), 2018 | 20 | 2018 |
| Learning to Learn the Future: Modeling Concept Drifts in Time Series Prediction X You, M Zhang, D Ding, F Feng, Y Huang 30th ACM International Conference on Information and Knowledge Management (CIKM), 2021 | 19 | 2021 |
| Enhancing Time Series Predictors with Generalized Extreme Value Loss M Zhang, D Ding, M Pan, Xudong, Yang IEEE Transactions on Knowledge and Data Engineering (TKDE), 2021 | 11 | 2021 |
| Towards Backdoor Attack on Deep Learning based Time Series Classification D Ding, M Zhang, H Yuanmin, F Fuli, J Erling, P Xudong, Y Min IEEE International Conference on Data Engineering (ICDE), 2022 | 9 | 2022 |
| Theoretical Analysis of Image-to-Image Translation with Adversarial Learning X Pan, M Zhang, D Ding 35th International Conference on Machine Learning (ICML), 2018 | 8 | 2018 |
| A Geometrical Perspective on Image Style Transfer with Adversarial Learning X Pan, M Zhang, D Ding, M Yang IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020 | 7 | 2020 |
| Black-box adversarial attack on time series classification D Ding, M Zhang, F Feng, Y Huang, E Jiang, M Yang Proceedings of the AAAI Conference on Artificial Intelligence 37 (6), 7358-7368, 2023 | 4 | 2023 |
| Anti-fakeu: Defending shilling attacks on graph neural network based recommender model X You, C Li, D Ding, M Zhang, F Feng, X Pan, M Yang Proceedings of the ACM Web Conference 2023, 938-948, 2023 | 4 | 2023 |
| MaSS: Model-agnostic, Semantic and Stealthy Data Poisoning Attack on Knowledge Graph Embedding Y XIaoyu, S Beina, D Daizong, Z Mi, P Xudong, Y Min, F Fuli 2023 World Wide Web Conference (WWW), 2023 | 4 | 2023 |
| A Deep Learning Framework for Self-evolving Hierarchical Community Detection D Ding, M Zhang, H Wang, X Pan, M Yang, X He 30th ACM International Conference on Information and Knowledge Management (CIKM), 2021 | 4 | 2021 |
| Improving the Robustness of Wasserstein Embedding by Adversarial PAC-Bayesian Learning D Ding, M Zhang, X Pan, M Yang, X He Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI), 2020 | 4 | 2020 |
| Modeling Personalized Out-of-Town Distances in Location Recommendation D Ding, M Zhang, X Pan, M Yang, X He 20th IEEE International Conference on Data Mining (ICDM), 2020 | 4 | 2020 |
| Uplift Modeling for Target User Attacks on Recommender Systems W Wang, C Wang, F Feng, W Shi, D Ding, TS Chua Proceedings of the ACM on Web Conference 2024, 3343-3354, 2024 | 1 | 2024 |
| CAP: Robust Point Cloud Classification via Semantic and Structural Modeling D Ding, J Erling, H Yuanmin, Z Mi, L Wenxuan, Y Min Conference on Computer Vision and Pattern Recognition (CVPR), 2023 | 1 | 2023 |
| CausalPC: Improving the Robustness of Point Cloud Classification by Causal Effect Identification Y Huang, M Zhang, D Ding, E Jiang, Z Wang, M Yang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | | 2024 |
Min Yang (杨珉)Professor, School of Computer Science and Technology, Fudan University在 fudan.edu.cn 的电子邮件经过验证
