15 citations · 36 across the 10 of their papers we have counts for
6 papers · 1 filter
Principal Eigenvalue Regularization for Improved Worst-Class Certified Robustness of Smoothed Classifiers
Gaojie Jin, Tianjin Huang, Ronghui Mu +1
Recent studies have identified a critical challenge in deep neural networks (DNNs) known as ``robust fairness", where models exhibit significant disparities in robust accuracy acro…
Trustworthy Text-to-Image Diffusion Models: A Timely and Focused Survey
Yi Zhang, Zhen Chen, Chih-Hong Cheng +6
Text-to-Image (T2I) Diffusion Models (DMs) have garnered widespread attention for their impressive advancements in image generation. However, their growing popularity has raised et…
Data Augmentation for Continual RL via Adversarial Gradient Episodic Memory
Sihao Wu, Xingyu Zhao, Xiaowei Huang
Data efficiency of learning, which plays a key role in the Reinforcement Learning (RL) training process, becomes even more important in continual RL with sequential environments. I…
Privacy-Preserving Distributed Learning for Residential Short-Term Load Forecasting
Yi Dong, Yingjie Wang, Mariana Gama +3
In the realm of power systems, the increasing involvement of residential users in load forecasting applications has heightened concerns about data privacy. Specifically, the load d…
ReRoGCRL: Representation-based Robustness in Goal-Conditioned Reinforcement Learning
Xiangyu Yin, Sihao Wu, Jiaxu Liu +4
While Goal-Conditioned Reinforcement Learning (GCRL) has gained attention, its algorithmic robustness against adversarial perturbations remains unexplored. The attacks and robust r…
Reward Certification for Policy Smoothed Reinforcement Learning
Ronghui Mu, Leandro Soriano Marcolino, Tianle Zhang +3
Reinforcement Learning (RL) has achieved remarkable success in safety-critical areas, but it can be weakened by adversarial attacks. Recent studies have introduced "smoothed polici…