Chen Dan

Affiliations:
  • Carnegie Mellon University, Pittsburgh, PA, USA


According to our database1, Chen Dan authored at least 19 papers between 2015 and 2024.

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Bibliography

2024
Distributional Adversarial Loss.
CoRR, 2024

2023
Understanding Why Generalized Reweighting Does Not Improve Over ERM.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Fundamental Limits and Tradeoffs in Invariant Representation Learning.
J. Mach. Learn. Res., 2022

2021
Boosted CVaR Classification.
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.
Proceedings of the 38th International Conference on Machine Learning, 2021

Learning Complexity of Simulated Annealing.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Sharp Statistical Guarantees for Adversarially Robust Gaussian Classification.
CoRR, 2020

Class-Weighted Classification: Trade-offs and Robust Approaches.
Proceedings of the 37th International Conference on Machine Learning, 2020

Sharp Statistical Guaratees for Adversarially Robust Gaussian Classification.
Proceedings of the 37th International Conference on Machine Learning, 2020

MACER: Attack-free and Scalable Robust Training via Maximizing Certified Radius.
Proceedings of the 8th International Conference on Learning Representations, 2020

Learning Sparse Nonparametric DAGs.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Adversarially Robust Generalization Just Requires More Unlabeled Data.
CoRR, 2019

Optimal Analysis of Subset-Selection Based L_p Low-Rank Approximation.
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.
Proceedings of the 27th Annual European Symposium on Algorithms, 2019

2018
Sample Complexity of Nonparametric Semi-Supervised Learning.
CoRR, 2018

Identifiability of Nonparametric Mixture Models and Bayes Optimal Clustering.
CoRR, 2018

The Sample Complexity of Semi-Supervised Learning with Nonparametric Mixture Models.
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.
Proceedings of the 43rd International Symposium on Mathematical Foundations of Computer Science, 2018

2015
On Low Rank Approximation of Binary Matrices.
CoRR, 2015


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