Chen Dan

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Pradeep RavikumarProfessor, School of Computer Science, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Runtian ZhaiPhD Student, Carnegie Mellon UniversityVerified email at cmu.edu
Bryon AragamUniversity of ChicagoVerified email at chicagobooth.edu
Eric XingPresident at Mohamed bin Zayed University of AI, Professor of Computer Science, Carnegie Mellon UVerified email at cs.cmu.edu
Liwei WangProfessor, Peking UniversityVerified email at cis.pku.edu.cn
Di HePeking UniversityVerified email at pku.edu.cn
Xun ZhengCarnegie Mellon UniversityVerified email at andrew.cmu.edu
Tianle CaiPhD Student, Princeton UniversityVerified email at princeton.edu
John HopcroftCornell UniversityVerified email at cs.cornell.edu
Kun HeProfessor, Huazhong University of Science and TechnologyVerified email at hust.edu.cn
Huan ZhangPostdoctoral Researcher at Carnegie Mellon University (CMU)Verified email at cs.cmu.edu
Cho-Jui HsiehUniversity of California, Los AngelesVerified email at cs.ucla.edu
Boqing GongResearch Scientist, GoogleVerified email at google.com
Yuchen ZhouStatistics and Data Science, Wharton School, University of PennsylvaniaVerified email at wharton.upenn.edu
Avrim BlumProfessor and Chief Academic Officer, Toyota Technological Institute at ChicagoVerified email at ttic.edu
Yuting WeiStatistics and Data Science at Wharton, University of PennsylvaniaVerified email at wharton.upenn.edu
Hongyang ZhangAssistant Professor of Computer Science, University of Waterloo, Vector InstituteVerified email at uwaterloo.ca
Ziyu XuCarnegie Mellon UniversityVerified email at cs.cmu.edu
Justin KhimApplied scientist at AmazonVerified email at amazon.com
Kristoffer Arnsfelt HansenAssociate Professor, Department of Computer Science, Aarhus UniversityVerified email at cs.au.dk

Chen Dan

Postdoctral Researcher, Toyota Technological Institute at Chicago

Verified email at ttic.edu - Homepage

Statistical Learning Theory


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Learning sparse nonparametric dags X Zheng, C Dan, B Aragam, P Ravikumar, E Xing International Conference on Artificial Intelligence and Statistics, 3414-3425, 2020	155	2020
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	118	2019
Macer: Attack-free and scalable robust training via maximizing certified radius R Zhai, C Dan, D He, H Zhang, B Gong, P Ravikumar, CJ Hsieh, L Wang 2020 International Conference on Learning Representations (ICLR 2020), 2020	117	2020
Sharp Statistical Guarantees for Adversarially Robust Gaussian Classification C Dan, Y Wei, P Ravikumar International Conference on Machine Learning 2020, 2020	36	2020
Identifiability of nonparametric mixture models and bayes optimal clustering B Aragam, C Dan, P Ravikumar, EP Xing Annals of Statistics 2019, 2018	26	2018
Doro: Distributional and outlier robust optimization R Zhai, C Dan, Z Kolter, P Ravikumar International Conference on Machine Learning, 12345-12355, 2021	24	2021
Class-Weighted Classification: Trade-offs and Robust Approaches Z Xu, C Dan, J Khim, P Ravikumar arXiv preprint arXiv:2005.12914, 2020	23	2020
Low Rank Approximation of Binary Matrices: Column Subset Selection and Generalizations C Dan, KA Hansen, H Jiang, L Wang, Y Zhou 43rd International Symposium on Mathematical Foundations of Computer …, 2015	19	2015
Learning Complexity of Simulated Annealing A Blum, C Dan, S Seddighin https://arxiv.org/abs/2003.02981v2, 2020	17	2020
Fundamental limits and tradeoffs in invariant representation learning H Zhao, C Dan, B Aragam, TS Jaakkola, GJ Gordon, P Ravikumar Journal of Machine Learning Research 23 (340), 1-49, 2022	12	2022
Optimal Analysis of Subset-Selection Based L_p Low-Rank Approximation C Dan, H Wang, H Zhang, Y Zhou, PK Ravikumar Advances in Neural Information Processing Systems, 2541-2552, 2019	12	2019
Understanding why generalized reweighting does not improve over erm R Zhai, C Dan, Z Kolter, P Ravikumar arXiv preprint arXiv:2201.12293, 2022	8	2022
Bilu-Linial stability, certified algorithms and the Independent Set problem H Angelidakis, P Awasthi, A Blum, V Chatziafratis, C Dan 27th Annual European Symposium on Algorithms (ESA 2019), 2018	8	2018
Boosted cvar classification R Zhai, C Dan, A Suggala, JZ Kolter, P Ravikumar Advances in Neural Information Processing Systems 34, 21860-21871, 2021	6	2021
The sample complexity of semi-supervised learning with nonparametric mixture models C Dan, L Leqi, B Aragam, PK Ravikumar, EP Xing Advances in Neural Information Processing Systems, 9321-9332, 2018	5	2018
Optimal analysis of subset-selection based ℓ_p low-rank approximation C Dan, H Wang, H Zhang, Y Zhou, P Ravikumar Proceedings of the 33rd International Conference on Neural Information …, 2019	1	2019
Statistical Learning under Adversarial Distribution Shift C Dan Carnegie Mellon University, 2021		2021
Sample Complexity of Nonparametric Semi-Supervised Learning C Dan, L Leqi, B Aragam, P Ravikumar, EP Xing arXiv preprint arXiv:1809.03073, 2018		2018
Understanding Overfitting in Reweighting Algorithms for Worst-group Performance R Zhai, C Dan, JZ Kolter, PK Ravikumar

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