Zhun Deng

Orcid: 0009-0002-3785-8513

According to our database¹, Zhun Deng authored at least 33 papers between 2017 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of three.

Timeline

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On csauthors.net:

Bibliography

2024

Provable Multi-Party Reinforcement Learning with Diverse Human Feedback.

[BibT_eX]

[DOI]

CoRR, 2024

Can AI Be as Creative as Humans?

[BibT_eX]

[DOI]

CoRR, 2024

2023

Learning and Forgetting Unsafe Examples in Large Language Models.

[BibT_eX]

[DOI]

CoRR, 2023

Prompt Risk Control: A Rigorous Framework for Responsible Deployment of Large Language Models.

[BibT_eX]

[DOI]

CoRR, 2023

Analyzing and Mitigating Object Hallucination in Large Vision-Language Models.

[BibT_eX]

[DOI]

CoRR, 2023

Last-Layer Fairness Fine-tuning is Simple and Effective for Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2023

HappyMap: A Generalized Multi-calibration Method.

[BibT_eX]

[DOI]

Zhun Deng

Cynthia Dwork

Linjun Zhang

CoRR, 2023

PICProp: Physics-Informed Confidence Propagation for Uncertainty Quantification.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Distribution-Free Statistical Dispersion Control for Societal Applications.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

HappyMap : A Generalized Multicalibration Method.

[BibT_eX]

[DOI]

Zhun Deng

Cynthia Dwork

Linjun Zhang

Proceedings of the 14th Innovations in Theoretical Computer Science Conference, 2023

How Does Information Bottleneck Help Deep Learning?

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Quantile Risk Control: A Flexible Framework for Bounding the Probability of High-Loss Predictions.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

FIFA: Making Fairness More Generalizable in Classifiers Trained on Imbalanced Data.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Decision-Aware Conditional GANs for Time Series Data.

[BibT_eX]

[DOI]

Proceedings of the 4th ACM International Conference on AI in Finance, 2023

Understanding Multimodal Contrastive Learning and Incorporating Unpaired Data.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Reinforcement Learning with Stepwise Fairness Constraints.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Understanding Dynamics of Nonlinear Representation Learning and Its Application.

[BibT_eX]

[DOI]

Kenji Kawaguchi

Linjun Zhang

Zhun Deng

Neural Comput., 2022

Investigating Fairness Disparities in Peer Review: A Language Model Enhanced Approach.

[BibT_eX]

[DOI]

CoRR, 2022

When and How Mixup Improves Calibration.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Robustness Implies Generalization via Data-Dependent Generalization Bounds.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

An Unconstrained Layer-Peeled Perspective on Neural Collapse.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Scaffolding Sets.

[BibT_eX]

[DOI]

CoRR, 2021

The Power of Contrast for Feature Learning: A Theoretical Analysis.

[BibT_eX]

[DOI]

CoRR, 2021

Adversarial Training Helps Transfer Learning via Better Representations.

[BibT_eX]

[DOI]

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

Toward Better Generalization Bounds with Locally Elastic Stability.

[BibT_eX]

[DOI]

Zhun Deng

Hangfeng He

Weijie J. Su

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

How Does Mixup Help With Robustness and Generalization?

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Learning Representations, 2021

How Shrinking Gradient Noise Helps the Performance of Neural Networks.

[BibT_eX]

[DOI]

Zhun Deng

Jiaoyang Huang

Kenji Kawaguchi

Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

Improving Adversarial Robustness via Unlabeled Out-of-Domain Data.

[BibT_eX]

[DOI]

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

2020

Representation via Representations: Domain Generalization via Adversarially Learned Invariant Representations.

[BibT_eX]

[DOI]

CoRR, 2020

Towards Understanding the Dynamics of the First-Order Adversaries.

[BibT_eX]

[DOI]

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

Interpreting Robust Optimization via Adversarial Influence Functions.

[BibT_eX]

[DOI]

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

2019

Architecture Selection via the Trade-off Between Accuracy and Robustness.

[BibT_eX]

[DOI]

CoRR, 2019

2017

The number of independent sets in hexagonal graphs.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE International Symposium on Information Theory, 2017

Zhun Deng

Timeline

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On csauthors.net:

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