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 | 3151 | 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 | 2196 | 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 | 611 | 2017 |
Automated Machine Learning: From Principles to Practices Z Shen, Y Zhang, L Wei, H Zhao, Q Yao arXiv preprint, 2018 | 576* | 2018 |
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 | 307* | 2020 |
Loss-aware Binarization of Deep Networks L Hou, Q Yao, JT Kwok International Conference on Learning Representations, 2017 | 251 | 2017 |
Simple and automated negative sampling for knowledge graph embedding Y Zhang, Q Yao, L Chen The VLDB Journal 30 (2), 259-285, 2021 | 147* | 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 | 142* | 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 | 125* | 2024 |
Search to aggregate neighborhood for graph neural network H Zhao, Q Yao, W Tu International Conference on Data Engineering, 2021 | 115* | 2021 |
Efficient Neural Architecture Search via Proximal Iterations Q Yao, J Xu, WW Tu, Z Zhu AAAI Conference on Artificial Intelligence, 2020 | 113 | 2020 |
Bilinear Scoring Function Search for Knowledge Graph Learning Y Zhang, Q Yao, J Kwok IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022 | 99* | 2022 |
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 | 97 | 2019 |
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 | 96 | 2019 |
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 | 95 | 2020 |
Knowledge Graph Reasoning with Relational Directed Graph Y Zhang, Q Yao The Web Conference, 2022 | 86* | 2022 |
Efficient Inexact Proximal Gradient Algorithm for Nonconvex Problems Q Yao, JT Kwok, F Gao, W Chen, T Liu International Joint Conference on Artificial Intelligence, 2017 | 80 | 2017 |
Generalizing Tensor Decomposition for N-ary Relational Knowledge Bases Y Liu, Q Yao, Y Li The Web Conference, 2020 | 79 | 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 | 77 | 2020 |
Accelerated and Inexact Soft-Impute for Large-scale Matrix and Tensor Completion Q Yao, JT Kwok IEEE Transactions on Knowledge and Data Engineering 31 (9), 1665-1679, 2019 | 72 | 2019 |