Zhehui Chen

According to our database1, Zhehui Chen authored at least 13 papers between 2017 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2023
Invisible Watermarking for Audio Generation Diffusion Models.
Proceedings of the 5th IEEE International Conference on Trust, 2023

Robust Multi-Agent Reinforcement Learning via Adversarial Regularization: Theoretical Foundation and Stable Algorithms.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022
APIK: Active Physics-Informed Kriging Model with Partial Differential Equations.
SIAM/ASA J. Uncertain. Quantification, 2022

2021
Learning to Defend by Learning to Attack.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2019
On Computation and Generalization of Generative Adversarial Networks under Spectrum Control.
Proceedings of the 7th International Conference on Learning Representations, 2019

Learning to Defense by Learning to Attack.
Proceedings of the Deep Generative Models for Highly Structured Data, 2019

On Constrained Nonconvex Stochastic Optimization: A Case Study for Generalized Eigenvalue Decomposition.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
On Computation and Generalization of GANs with Spectrum Control.
CoRR, 2018

Learning to Defense by Learning to Attack.
CoRR, 2018

On Landscape of Lagrangian Functions and Stochastic Search for Constrained Nonconvex Optimization.
CoRR, 2018

Toward Deeper Understanding of Nonconvex Stochastic Optimization with Momentum using Diffusion Approximations.
CoRR, 2018

2017
Online Multiview Representation Learning: Dropping Convexity for Better Efficiency.
CoRR, 2017

Online Partial Least Square Optimization: Dropping Convexity for Better Efficiency and Scalability.
Proceedings of the 34th International Conference on Machine Learning, 2017


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