Wei-Wei Tu
Wei-Wei Tu
Nanjing University, ChaLearn
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Cited by
Cited by
Automated machine learning: methods, systems, challenges
F Hutter, L Kotthoff, J Vanschoren
Springer Nature, 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 ..., 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
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
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
Sadam: A variant of adam for strongly convex functions
G Wang, S Lu, W Tu, L Zhang
arXiv preprint arXiv:1905.02957, 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
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
Search to aggregate neighborhood for graph neural network
H Zhao, Q Yao, W Tu
arXiv preprint arXiv:2104.06608, 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
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
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
Learning for Tail Label Data: A Label-Specific Feature Approach.
T Wei, WW Tu, YF Li
IJCAI, 3842-3848, 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
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
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
Robust long-tailed learning under label noise
T Wei, JX Shi, WW Tu, YF Li
arXiv preprint arXiv:2108.11569, 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
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
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
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