| Generalizing from a few examples: A survey on few-shot learning Y Wang, Q Yao, JT Kwok, LM Ni ACM Computing Surveys 53 (3), 1-34, 2020 | 4809 | 2020 |
| Co-teaching: Robust Training Deep Neural Networks with Extremely Noisy Labels B Han, Q Yao, X Yu, G Niu, M Xu, W Hu, I Tsang, M Sugiyama Advance in Neural Information Processing Systems, 2018 | 3115 | 2018 |
| Automated Machine Learning: From Principles to Practices Z Shen, Y Zhang, L Wei, H Zhao, Q Yao arXiv preprint, 2018 | 728* | 2018 |
| Meta-graph based recommendation fusion over heterogeneous information networks H Zhao, Q Yao, J Li, Y Song, DL Lee ACM SIGKDD International Conference on Knowledge Discovery and Data Mining …, 2017 | 717 | 2017 |
| Non-local meets global: An iterative paradigm for hyperspectral image restoration W He, Q Yao, C Li, N Yokoya, Q Zhao, H Zhang, L Zhang IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (4), 2089-2107, 2020 | 451* | 2020 |
| Loss-aware Binarization of Deep Networks L Hou, Q Yao, JT Kwok International Conference on Learning Representations, 2017 | 283 | 2017 |
| Knowledge Graph Reasoning with Relational Directed Graph Y Zhang, Q Yao The Web Conference, 2022 | 215* | 2022 |
| Simple and automated negative sampling for knowledge graph embedding Y Zhang, Q Yao, L Chen The VLDB Journal 30 (2), 259-285, 2021 | 199* | 2021 |
| SIGUA: Forgetting May Make Learning with Noisy Labels More Robust B Han, G Niu, X Yu, Q Yao, M Xu, I Tsang, M Sugiyama International Conference on Machine Learning, 2020 | 196* | 2020 |
| Searching to Exploit Memorization Effect in Learning from Corrupted Labels Q Yao, H Yang, B Han, G Niu, J Kwok IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024 | 186* | 2024 |
| Search to aggregate neighborhood for graph neural network H Zhao, Q Yao, W Tu International Conference on Data Engineering, 2021 | 170* | 2021 |
| Simplify and Robustify Negative Sampling for Implicit Collaborative Filtering J Ding, Y Quan, Q Yao, Y Li, D Jin Annual Conference on Neural Information Processing Systems, 2020 | 157 | 2020 |
| Codabench: Flexible, easy-to-use, and reproducible meta-benchmark platform Z Xu, S Escalera, A Pavão, M Richard, WW Tu, Q Yao, H Zhao, I Guyon Patterns 3 (7), 2022 | 155 | 2022 |
| Large-Scale Low-Rank Matrix Learning with Nonconvex Regularizers Q Yao, JT Kwok, T Wang, TY Liu IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019 | 154* | 2019 |
| Bilinear Scoring Function Search for Knowledge Graph Learning Y Zhang, Q Yao, J Kwok IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023 | 141* | 2023 |
| Neural architecture search for GNN-based graph classification L Wei, H Zhao, Z He, Q Yao ACM Transactions on Information Systems 42 (1), 1-29, 2023 | 138* | 2023 |
| AutoCross: Automatic Feature Crossing for Tabular Data in Real-World Applications Y Luo, M Wang, H Zhou, Q Yao, WW Tu, Y Chen, Q Yang, W Dai ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2019 | 135 | 2019 |
| Efficient Neural Architecture Search via Proximal Iterations Q Yao, J Xu, WW Tu, Z Zhu AAAI Conference on Artificial Intelligence, 2020 | 134 | 2020 |
| Predicting Origin-Destination Flow via Multi-Perspective Graph Convolutional Network H Shi, Q Yao, Q Guo, Y Li, L Zhang, J Ye, Y Li, Y Liu IEEE International Conference on Data Engineering, 2020 | 120 | 2020 |
| Property-Aware Relation Networks for Few-Shot Molecular Property Prediction Q Yao, Z Shen, Y Wang, D Dou IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024 | 111 | 2024 |
James T. KwokProfessor of Computer Science and Engineering, Hong Kong University of Science and TechnologyVerified email at cse.ust.hk
