| Automated machine learning: methods, systems, challenges F Hutter, L Kotthoff, J Vanschoren Springer Nature, 2019 | 1240 | 2019 |
| Taking Human out of Learning Applications: A Survey on Automated Machine Learning YY Quanming Yao, Mengshuo Wang, Yuqiang Chen, Wenyuan Dai, Yu-Feng Li, Wei ... https://arxiv.org/abs/1810.13306, 2018 | 387* | 2018 |
| Analysis of the AutoML challenge series I Guyon, L Sun-Hosoya, M Boullé, HJ Escalante, S Escalera, Z Liu, ... Automated Machine Learning 177, 2019 | 101 | 2019 |
| Efficient neural architecture search via proximal iterations Q Yao, J Xu, WW Tu, Z Zhu Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 6664-6671, 2020 | 76 | 2020 |
| Autocross: Automatic feature crossing for tabular data in real-world applications Y Luo, M Wang, H Zhou, Q Yao, WW Tu, Y Chen, W Dai, Q Yang Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019 | 65 | 2019 |
| Sadam: A variant of adam for strongly convex functions G Wang, S Lu, W Tu, L Zhang arXiv preprint arXiv:1905.02957, 2019 | 35 | 2019 |
| Towards AutoML in the presence of Drift: first results JG Madrid, HJ Escalante, EF Morales, WW Tu, Y Yu, L Sun-Hosoya, ... arXiv preprint arXiv:1907.10772, 2019 | 30 | 2019 |
| Towards automated semi-supervised learning YF Li, H Wang, T Wei, WW Tu Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 4237-4244, 2019 | 30 | 2019 |
| Search to aggregate neighborhood for graph neural network H Zhao, Q Yao, W Tu arXiv preprint arXiv:2104.06608, 2021 | 29 | 2021 |
| Multi-fidelity automatic hyper-parameter tuning via transfer series expansion YQ Hu, Y Yu, WW Tu, Q Yang, Y Chen, W Dai Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 3846-3853, 2019 | 26 | 2019 |
| COVID-19 asymptomatic infection estimation Y Yu, YR Liu, FM Luo, WW Tu, DC Zhan, G Yu, ZH Zhou medRxiv, 2020.04. 19.20068072, 2020 | 23 | 2020 |
| Towards automated deep learning: Analysis of the autodl challenge series 2019 Z Liu, Z Xu, S Rajaa, M Madadi, JCSJ Junior, S Escalera, A Pavao, ... NeurIPS 2019 Competition and Demonstration Track, 242-252, 2020 | 20 | 2020 |
| Learning for Tail Label Data: A Label-Specific Feature Approach. T Wei, WW Tu, YF Li IJCAI, 3842-3848, 2019 | 17 | 2019 |
| Dual adaptivity: A universal algorithm for minimizing the adaptive regret of convex functions L Zhang, G Wang, WW Tu, W Jiang, ZH Zhou Advances in Neural Information Processing Systems 34, 24968-24980, 2021 | 16 | 2021 |
| Network on network for tabular data classification in real-world applications Y Luo, H Zhou, WW Tu, Y Chen, W Dai, Q Yang Proceedings of the 43rd International ACM SIGIR Conference on Research and …, 2020 | 15 | 2020 |
| Autocv challenge design and baseline results Z Liu, I Guyon, JJ Junior, M Madadi, S Escalera, A Pavao, HJ Escalante, ... CAp 2019-Conférence sur l'Apprentissage Automatique, 2019 | 15 | 2019 |
| Robust long-tailed learning under label noise T Wei, JX Shi, WW Tu, YF Li arXiv preprint arXiv:2108.11569, 2021 | 14 | 2021 |
| Automl@ neurips 2018 challenge: Design and results HJ Escalante, WW Tu, I Guyon, DL Silver, E Viegas, Y Chen, W Dai, ... The NeurIPS'18 Competition: From Machine Learning to Intelligent …, 2020 | 14 | 2020 |
| Projection-free Distributed Online Convex Optimization with $ O (\sqrtT) $ Communication Complexity Y Wan, WW Tu, L Zhang International Conference on Machine Learning, 9818-9828, 2020 | 13 | 2020 |
| Privacy-Preserving Stacking with Application to Cross-organizational Diabetes Prediction. Q Yao, X Guo, JT Kwok, WW Tu, Y Chen, W Dai, Q Yang IJCAI, 4114-4120, 2019 | 12 | 2019 |
Quanming YaoAssistant Professor, EE Department, Tsinghua UniversityVerified email at tsinghua.edu.cn
