Zhun Deng

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 54

Top Topics

Robust Optimization

Calibration Method

Invariant Representations

Top Venues

Publications

Haonan Wang, James Zou, Michael Mozer, Anirudh Goyal, Alex Lamb, Linjun Zhang, Weijie J. Su, Zhun Deng, Michael Qizhe Xie, Hannah Brown, Kenji Kawaguchi
Can AI Be as Creative as Humans? CoRR (2024)
Thomas P. Zollo, Todd Morrill, Zhun Deng, Jake Snell, Toniann Pitassi, Richard S. Zemel
Prompt Risk Control: A Rigorous Framework for Responsible Deployment of Large Language Models. ICLR (2024)
Huiying Zhong, Zhun Deng, Weijie J. Su, Zhiwei Steven Wu, Linjun Zhang
Provable Multi-Party Reinforcement Learning with Diverse Human Feedback. CoRR (2024)
Yiyang Zhou, Chenhang Cui, Jaehong Yoon, Linjun Zhang, Zhun Deng, Chelsea Finn, Mohit Bansal, Huaxiu Yao
Analyzing and Mitigating Object Hallucination in Large Vision-Language Models. ICLR (2024)
Jiachen T. Wang, Zhun Deng, Hiroaki Chiba-Okabe, Boaz Barak, Weijie J. Su
An Economic Solution to Copyright Challenges of Generative AI. CoRR (2024)
Jiachen Zhao, Zhun Deng, David Madras, James Zou, Mengye Ren
Learning and Forgetting Unsafe Examples in Large Language Models. CoRR (2023)
He Sun, Zhun Deng, Hui Chen, David C. Parkes
Decision-Aware Conditional GANs for Time Series Data. ICAIF (2023)
Yuzhen Mao, Zhun Deng, Huaxiu Yao, Ting Ye, Kenji Kawaguchi, James Zou
Last-Layer Fairness Fine-tuning is Simple and Effective for Neural Networks. CoRR (2023)
Zhun Deng, Cynthia Dwork, Linjun Zhang
HappyMap : A Generalized Multicalibration Method. ITCS (2023)
Ryumei Nakada, Halil Ibrahim Gulluk, Zhun Deng, Wenlong Ji, James Zou, Linjun Zhang
Understanding Multimodal Contrastive Learning and Incorporating Unpaired Data. AISTATS (2023)
Jake Snell, Thomas P. Zollo, Zhun Deng, Toniann Pitassi, Richard S. Zemel
Quantile Risk Control: A Flexible Framework for Bounding the Probability of High-Loss Predictions. ICLR (2023)
Zhun Deng, He Sun, Steven Wu, Linjun Zhang, David C. Parkes
Reinforcement Learning with Stepwise Fairness Constraints. AISTATS (2023)
Zhun Deng, Thomas P. Zollo, Jake Snell, Toniann Pitassi, Richard S. Zemel
Distribution-Free Statistical Dispersion Control for Societal Applications. NeurIPS (2023)
Kenji Kawaguchi, Zhun Deng, Xu Ji, Jiaoyang Huang
How Does Information Bottleneck Help Deep Learning? ICML (2023)
Zhun Deng, Jiayao Zhang, Linjun Zhang, Ting Ye, Yates Coley, Weijie J. Su, James Zou
FIFA: Making Fairness More Generalizable in Classifiers Trained on Imbalanced Data. ICLR (2023)
Kenji Kawaguchi, Zhun Deng, Xu Ji, Jiaoyang Huang
How Does Information Bottleneck Help Deep Learning? CoRR (2023)
Ryumei Nakada, Halil Ibrahim Gulluk, Zhun Deng, Wenlong Ji, James Zou, Linjun Zhang
Understanding Multimodal Contrastive Learning and Incorporating Unpaired Data. CoRR (2023)
Thomas P. Zollo, Todd Morrill, Zhun Deng, Jake C. Snell, Toniann Pitassi, Richard S. Zemel
Prompt Risk Control: A Rigorous Framework for Responsible Deployment of Large Language Models. CoRR (2023)
Zhun Deng, Cynthia Dwork, Linjun Zhang
HappyMap: A Generalized Multi-calibration Method. CoRR (2023)
Qianli Shen, Wai Hoh Tang, Zhun Deng, Apostolos F. Psaros, Kenji Kawaguchi
PICProp: Physics-Informed Confidence Propagation for Uncertainty Quantification. CoRR (2023)
Yiyang Zhou, Chenhang Cui, Jaehong Yoon, Linjun Zhang, Zhun Deng, Chelsea Finn, Mohit Bansal, Huaxiu Yao
Analyzing and Mitigating Object Hallucination in Large Vision-Language Models. CoRR (2023)
Qianli Shen, Wai Hoh Tang, Zhun Deng, Apostolos F. Psaros, Kenji Kawaguchi
PICProp: Physics-Informed Confidence Propagation for Uncertainty Quantification. NeurIPS (2023)
Zhun Deng, Thomas P. Zollo, Jake C. Snell, Toniann Pitassi, Richard S. Zemel
Distribution-Free Statistical Dispersion Control for Societal Applications. CoRR (2023)
Jake C. Snell, Thomas P. Zollo, Zhun Deng, Toniann Pitassi, Richard S. Zemel
Quantile Risk Control: A Flexible Framework for Bounding the Probability of High-Loss Predictions. CoRR (2022)
Zhun Deng, Jiayao Zhang, Linjun Zhang, Ting Ye, Yates Coley, Weijie J. Su, James Zou
FIFA: Making Fairness More Generalizable in Classifiers Trained on Imbalanced Data. CoRR (2022)
Jiayao Zhang, Hongming Zhang, Zhun Deng, Dan Roth
Investigating Fairness Disparities in Peer Review: A Language Model Enhanced Approach. CoRR (2022)
Linjun Zhang, Zhun Deng, Kenji Kawaguchi, James Zou
When and How Mixup Improves Calibration. ICML (2022)
Wenlong Ji, Yiping Lu, Yiliang Zhang, Zhun Deng, Weijie J. Su
An Unconstrained Layer-Peeled Perspective on Neural Collapse. ICLR (2022)
Kenji Kawaguchi, Linjun Zhang, Zhun Deng
Understanding Dynamics of Nonlinear Representation Learning and Its Application. Neural Comput. 34 (4) (2022)
Zhun Deng, He Sun, Zhiwei Steven Wu, Linjun Zhang, David C. Parkes
Reinforcement Learning with Stepwise Fairness Constraints. CoRR (2022)
Kenji Kawaguchi, Zhun Deng, Kyle Luh, Jiaoyang Huang
Robustness Implies Generalization via Data-Dependent Generalization Bounds. ICML (2022)
Kenji Kawaguchi, Zhun Deng, Kyle Luh, Jiaoyang Huang
Robustness Implies Generalization via Data-Dependent Generalization Bounds. CoRR (2022)
Linjun Zhang, Zhun Deng, Kenji Kawaguchi, James Zou
When and How Mixup Improves Calibration. CoRR (2021)
Zhun Deng, Linjun Zhang, Kailas Vodrahalli, Kenji Kawaguchi, James Zou
Adversarial Training Helps Transfer Learning via Better Representations. CoRR (2021)
Zhun Deng, Linjun Zhang, Kailas Vodrahalli, Kenji Kawaguchi, James Y. Zou
Adversarial Training Helps Transfer Learning via Better Representations. NeurIPS (2021)
Wenlong Ji, Zhun Deng, Ryumei Nakada, James Zou, Linjun Zhang
The Power of Contrast for Feature Learning: A Theoretical Analysis. CoRR (2021)
Kenji Kawaguchi, Linjun Zhang, Zhun Deng
Understanding Dynamics of Nonlinear Representation Learning and Its Application. CoRR (2021)
Zhun Deng, Linjun Zhang, Amirata Ghorbani, James Zou
Improving Adversarial Robustness via Unlabeled Out-of-Domain Data. AISTATS (2021)
Wenlong Ji, Yiping Lu, Yiliang Zhang, Zhun Deng, Weijie J. Su
An Unconstrained Layer-Peeled Perspective on Neural Collapse. CoRR (2021)
Linjun Zhang, Zhun Deng, Kenji Kawaguchi, Amirata Ghorbani, James Zou
How Does Mixup Help With Robustness and Generalization? ICLR (2021)
Zhun Deng, Jiaoyang Huang, Kenji Kawaguchi
How Shrinking Gradient Noise Helps the Performance of Neural Networks. IEEE BigData (2021)
Zhun Deng, Hangfeng He, Weijie J. Su
Toward Better Generalization Bounds with Locally Elastic Stability. ICML (2021)
Maya Burhanpurkar, Zhun Deng, Cynthia Dwork, Linjun Zhang
Scaffolding Sets. CoRR (2021)
Linjun Zhang, Zhun Deng, Kenji Kawaguchi, Amirata Ghorbani, James Y. Zou
How Does Mixup Help With Robustness and Generalization? CoRR (2020)
Zhun Deng, Hangfeng He, Jiaoyang Huang, Weijie J. Su
Towards Understanding the Dynamics of the First-Order Adversaries. ICML (2020)
Zhun Deng, Hangfeng He, Jiaoyang Huang, Weijie J. Su
Towards Understanding the Dynamics of the First-Order Adversaries. CoRR (2020)
Zhun Deng, Cynthia Dwork, Jialiang Wang, Linjun Zhang
Interpreting Robust Optimization via Adversarial Influence Functions. CoRR (2020)
Zhun Deng, Hangfeng He, Weijie J. Su
Toward Better Generalization Bounds with Locally Elastic Stability. CoRR (2020)
Zhun Deng, Linjun Zhang, Amirata Ghorbani, James Y. Zou
Improving Adversarial Robustness via Unlabeled Out-of-Domain Data. CoRR (2020)
Zhun Deng, Cynthia Dwork, Jialiang Wang, Linjun Zhang
Interpreting Robust Optimization via Adversarial Influence Functions. ICML (2020)
He Sun, Zhun Deng, Hui Chen, David C. Parkes
Decision-Aware Conditional GANs for Time Series Data. CoRR (2020)
Zhun Deng, Frances Ding, Cynthia Dwork, Rachel Hong, Giovanni Parmigiani, Prasad Patil, Pragya Sur
Representation via Representations: Domain Generalization via Adversarially Learned Invariant Representations. CoRR (2020)
Zhun Deng, Cynthia Dwork, Jialiang Wang, Yao Zhao
Architecture Selection via the Trade-off Between Accuracy and Robustness. CoRR (2019)
Zhun Deng, Jie Ding, Kathryn Heal, Vahid Tarokh
The number of independent sets in hexagonal graphs. ISIT (2017)