Chen Dan
Chen Dan
PhD Student, Computer Science Department, Carnegie Mellon University
Verified email at - Homepage
Cited by
Cited by
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
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
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
arXiv preprint arXiv:2001.02378, 2020
Learning sparse nonparametric dags
X Zheng, C Dan, B Aragam, P Ravikumar, E Xing
International Conference on Artificial Intelligence and Statistics, 3414-3425, 2020
Identifiability of nonparametric mixture models and bayes optimal clustering
B Aragam, C Dan, P Ravikumar, EP Xing
Annals of Statistics 2019, 2018
Optimal Analysis of Subset-Selection Based L_p Low Rank Approximation
C Dan, H Wang, H Zhang, Y Zhou, P Ravikumar
Advances in Neural Information Processing Systems (NeurIPS 2019), 2019
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
Sharp Statistical Guarantees for Adversarially Robust Gaussian Classification
C Dan, Y Wei, P Ravikumar
arXiv preprint arXiv:2006.16384, 2020
Class-Weighted Classification: Trade-offs and Robust Approaches
Z Xu, C Dan, J Khim, P Ravikumar
arXiv preprint arXiv:2005.12914, 2020
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 (NeurIPS 2018), 9321-9332, 2018
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