On Low Rank Approximation of Binary Matrices. - Chen Dan 001; Kristoffer Arnsfelt Hansen; He Jiang; Liwei Wang 001; Yuchen Zhou (CoRR, 2015)

Low Rank Approximation of Binary Matrices: Column Subset Selection and Generalizations. - Chen Dan 001; Kristoffer Arnsfelt Hansen; He Jiang; Liwei Wang 001; Yuchen Zhou (MFCS, 2018)

The Sample Complexity of Semi-Supervised Learning with Nonparametric Mixture Models. - Chen Dan 001; Liu Leqi; Bryon Aragam; Pradeep Ravikumar; Eric P. Xing (NeurIPS, 2018)

Identifiability of Nonparametric Mixture Models and Bayes Optimal Clustering. - Bryon Aragam; Chen Dan 001; Pradeep Ravikumar; Eric P. Xing (CoRR, 2018)

Sample Complexity of Nonparametric Semi-Supervised Learning. - Chen Dan 001; Liu Leqi; Bryon Aragam; Pradeep Ravikumar; Eric P. Xing (CoRR, 2018)

Bilu-Linial Stability, Certified Algorithms and the Independent Set Problem. - Haris Angelidakis; Pranjal Awasthi; Avrim Blum; Vaggos Chatziafratis; Chen Dan 001 (ESA, 2019)

Optimal Analysis of Subset-Selection Based L_p Low-Rank Approximation. - Chen Dan 001; Hong Wang; Hongyang Zhang 001; Yuchen Zhou; Pradeep Ravikumar (NeurIPS, 2019)

Adversarially Robust Generalization Just Requires More Unlabeled Data. - Runtian Zhai; Tianle Cai; Di He 001; Chen Dan 001; Kun He 001; John E. Hopcroft; Liwei Wang 001 (CoRR, 2019)

Learning Sparse Nonparametric DAGs. - Xun Zheng; Chen Dan 001; Bryon Aragam; Pradeep Ravikumar; Eric P. Xing (AISTATS, 2020)

MACER: Attack-free and Scalable Robust Training via Maximizing Certified Radius. - Runtian Zhai; Chen Dan 001; Di He 001; Huan Zhang 001; Boqing Gong; Pradeep Ravikumar; Cho-Jui Hsieh; Liwei Wang 001 (ICLR, 2020)

Sharp Statistical Guaratees for Adversarially Robust Gaussian Classification. - Chen Dan 001; Yuting Wei 001; Pradeep Ravikumar (ICML, 2020)

Class-Weighted Classification: Trade-offs and Robust Approaches. - Ziyu Xu 001; Chen Dan 001; Justin Khim; Pradeep Ravikumar (ICML, 2020)

Sharp Statistical Guarantees for Adversarially Robust Gaussian Classification. - Chen Dan 001; Yuting Wei 001; Pradeep Ravikumar (CoRR, 2020)

Learning Complexity of Simulated Annealing. - Avrim Blum; Chen Dan 001; Saeed Seddighin (AISTATS, 2021)

DORO: Distributional and Outlier Robust Optimization. - Runtian Zhai; Chen Dan 001; J. Zico Kolter; Pradeep Ravikumar (ICML, 2021)

Boosted CVaR Classification. - Runtian Zhai; Chen Dan 001; Arun Sai Suggala; J. Zico Kolter; Pradeep Ravikumar (NeurIPS, 2021)

Fundamental Limits and Tradeoffs in Invariant Representation Learning. - Han Zhao 002; Chen Dan 001; Bryon Aragam; Tommi S. Jaakkola; Geoffrey J. Gordon; Pradeep Ravikumar (J. Mach. Learn. Res., 2022)

Statistical Learning Under Adversarial Distribution Shift - Chen Dan 001 (2022)

Understanding Why Generalized Reweighting Does Not Improve Over ERM. - Runtian Zhai; Chen Dan 001; J. Zico Kolter; Pradeep Kumar Ravikumar (ICLR, 2023)

Distributional Adversarial Loss. - Saba Ahmadi; Siddharth Bhandari; Avrim Blum; Chen Dan 001; Prabhav Jain (AISTATS, 2025)