Tianle Cai

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Liwei WangProfessor, Peking UniversityVerified email at cis.pku.edu.cn
Di HePeking UniversityVerified email at pku.edu.cn
Shengjie LuoPhD Student, Peking UniversityVerified email at stu.pku.edu.cn
Ruiqi GaoPhD Student, Princeton UniversityVerified email at princeton.edu
Shuxin ZhengSenior Researcher, Microsoft Research AsiaVerified email at microsoft.com
Guolin KeDP TechnologyVerified email at microsoft.com
Tie-Yan LiuDistinguished Scientist, Microsoft | Assistant Managing Director, MSRA | IEEE Fellow | ACM FellowVerified email at microsoft.com
Jason D. LeeAssistant Professor of Electrical Engineering, Princeton UniversityVerified email at princeton.edu
Siyu ChenCarnegie Mellon UniversityVerified email at andrew.cmu.edu
Runtian ZhaiPhD Student, Carnegie Mellon UniversityVerified email at cmu.edu
Chen DanPhD Student, Computer Science Department, Carnegie Mellon UniversityVerified email at andrew.cmu.edu
John HopcroftCornell UniversityVerified email at cs.cornell.edu
Zhihua ZhangProfessor of Computer Science, Shanghai Jiao Tong UniversityVerified email at zju.edu.cn
Jikai HouPrinceton UniversityVerified email at princeton.edu
Cho-Jui HsiehUniversity of California, Los AngelesVerified email at cs.ucla.edu
Haochuan LiMITVerified email at mit.edu
Keyulu XuMITVerified email at mit.edu
Tiange LuoPeking UniversityVerified email at pku.edu.cn
Kai ZhengPeking UniversityVerified email at pku.edu.cn
Qi LeiAssociate Research Scholar at ECE Department, Princeton UniversityVerified email at princeton.edu

Tianle Cai

PhD Student, Princeton University

Verified email at princeton.edu - Homepage

Machine Learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Adversarially robust generalization just requires more unlabeled data R Zhai, T Cai, D He, C Dan, K He, J Hopcroft, L Wang arXiv preprint arXiv:1906.00555, 2019	84	2019
Do Transformers Really Perform Bad for Graph Representation? C Ying, T Cai, S Luo, S Zheng, G Ke, D He, Y Shen, TY Liu NeurIPS 2021, arXiv preprint arXiv:2106.05234, 2021	80	2021
Convergence of adversarial training in overparametrized neural networks R Gao, T Cai, H Li, CJ Hsieh, L Wang, JD Lee NeurIPS 2019 Spotlight, arXiv preprint arXiv:1906.07916, 13029-13040, 2019	67	2019
Graphnorm: A principled approach to accelerating graph neural network training T Cai, S Luo, K Xu, D He, T Liu, L Wang ICML 2021, arXiv preprint arXiv:2009.03294, 2020	43	2020
Gram-Gauss-Newton Method: Learning Overparameterized Neural Networks for Regression Problems T Cai, R Gao, J Hou, S Chen, D Wang, D He, Z Zhang, L Wang NeurIPS 2019 Beyond First Order Methods in ML Workshop, arXiv preprint arXiv …, 2019	30	2019
Sanity-Checking Pruning Methods: Random Tickets can Win the Jackpot J Su, Y Chen, T Cai, T Wu, R Gao, L Wang, JD Lee NeurIPS 2020, arXiv preprint arXiv:2009.11094, 2020	19	2020
Locally differentially private (contextual) bandits learning K Zheng, T Cai, W Huang, Z Li, L Wang NeurIPS 2020, arXiv preprint arXiv:2006.00701, 2020	16	2020
A Theory of Label Propagation for Subpopulation Shift T Cai, R Gao, JD Lee, Q Lei ICML 2021, arXiv preprint arXiv:2102.11203, 2021	12	2021
Towards Certifying L-infinity Robustness using Neural Networks with L-inf-dist Neurons B Zhang, T Cai, Z Lu, D He, L Wang ICML 2021, arXiv preprint arXiv:2102.05363, 12368-12379, 2021	9	2021
Defective Convolutional Networks T Luo, T Cai, M Zhang, S Chen, D He, L Wang arXiv preprint arXiv:1911.08432, 2019	9*	2019
Towards a Theoretical Framework of Out-of-Distribution Generalization H Ye, C Xie, T Cai, R Li, Z Li, L Wang NeurIPS 2021, arXiv preprint arXiv:2106.04496, 2021	8	2021
Stable, Fast and Accurate: Kernelized Attention with Relative Positional Encoding S Luo, S Li, T Cai, D He, D Peng, S Zheng, G Ke, L Wang, TY Liu NeurIPS 2021, arXiv preprint arXiv:2106.12566, 2021	6	2021

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