Chen Dan

According to our database, Chen Dan authored at least 19 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

Distributional Adversarial Loss.

Saba Ahmadi, Siddharth Bhandari, Avrim Blum, Chen Dan, Prabhav Jain

CoRR, 2024

2023

Understanding Why Generalized Reweighting Does Not Improve Over ERM.

Runtian Zhai, Chen Dan, J. Zico Kolter, Pradeep Kumar Ravikumar

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Fundamental Limits and Tradeoffs in Invariant Representation Learning.

Han Zhao, Chen Dan, Bryon Aragam, Tommi S. Jaakkola, Geoffrey J. Gordon, Pradeep Ravikumar

J. Mach. Learn. Res., 2022

2021

Boosted CVaR Classification.

Runtian Zhai, Chen Dan, Arun Sai Suggala, J. Zico Kolter, Pradeep Ravikumar

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

DORO: Distributional and Outlier Robust Optimization.

Runtian Zhai, Chen Dan, J. Zico Kolter, Pradeep Ravikumar

Proceedings of the 38th International Conference on Machine Learning, 2021

Learning Complexity of Simulated Annealing.

Avrim Blum, Chen Dan, Saeed Seddighin

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Sharp Statistical Guarantees for Adversarially Robust Gaussian Classification.

Chen Dan, Yuting Wei, Pradeep Ravikumar

CoRR, 2020

Class-Weighted Classification: Trade-offs and Robust Approaches.

Ziyu Xu, Chen Dan, Justin Khim, Pradeep Ravikumar

Proceedings of the 37th International Conference on Machine Learning, 2020

Sharp Statistical Guaratees for Adversarially Robust Gaussian Classification.

Chen Dan, Yuting Wei, Pradeep Ravikumar

Proceedings of the 37th International Conference on Machine Learning, 2020

MACER: Attack-free and Scalable Robust Training via Maximizing Certified Radius.

Runtian Zhai, Chen Dan, Di He, Huan Zhang, Boqing Gong, Pradeep Ravikumar, Cho-Jui Hsieh, Liwei Wang

Proceedings of the 8th International Conference on Learning Representations, 2020

Learning Sparse Nonparametric DAGs.

Xun Zheng, Chen Dan, Bryon Aragam, Pradeep Ravikumar, Eric P. Xing

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Adversarially Robust Generalization Just Requires More Unlabeled Data.

Runtian Zhai, Tianle Cai, Di He, Chen Dan, Kun He, John E. Hopcroft, Liwei Wang

CoRR, 2019

Optimal Analysis of Subset-Selection Based L_p Low-Rank Approximation.

Chen Dan, Hong Wang, Hongyang Zhang, Yuchen Zhou, Pradeep Ravikumar

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Bilu-Linial Stability, Certified Algorithms and the Independent Set Problem.

Haris Angelidakis, Pranjal Awasthi, Avrim Blum, Vaggos Chatziafratis, Chen Dan

Proceedings of the 27th Annual European Symposium on Algorithms, 2019

2018

Sample Complexity of Nonparametric Semi-Supervised Learning.

Chen Dan, Liu Leqi, Bryon Aragam, Pradeep Ravikumar, Eric P. Xing

CoRR, 2018

Identifiability of Nonparametric Mixture Models and Bayes Optimal Clustering.

Bryon Aragam, Chen Dan, Pradeep Ravikumar, Eric P. Xing

CoRR, 2018

The Sample Complexity of Semi-Supervised Learning with Nonparametric Mixture Models.

Chen Dan, Liu Leqi, Bryon Aragam, Pradeep Ravikumar, Eric P. Xing

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Low Rank Approximation of Binary Matrices: Column Subset Selection and Generalizations.

Chen Dan, Kristoffer Arnsfelt Hansen, He Jiang, Liwei Wang, Yuchen Zhou

Proceedings of the 43rd International Symposium on Mathematical Foundations of Computer Science, 2018

2015

On Low Rank Approximation of Binary Matrices.

Chen Dan, Kristoffer Arnsfelt Hansen, He Jiang, Liwei Wang, Yuchen Zhou

CoRR, 2015