activity
20202023
most citedFairNeuron: Improving Deep Neural Network Fairness with Adversary Games on Selective Neurons

4 citations · 12 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CR2023★ 1 cited

Intellectual Property Protection of Diffusion Models via the Watermark Diffusion Process

Sen Peng, Yufei Chen, Cong Wang +1

Diffusion models have rapidly become a vital part of deep generative architectures, given today's increasing demands. Obtaining large, high-performance diffusion models demands sig…

cs.LG2023

CILIATE: Towards Fairer Class-based Incremental Learning by Dataset and Training Refinement

Xuanqi Gao, Juan Zhai, Shiqing Ma +3

Due to the model aging problem, Deep Neural Networks (DNNs) need updates to adjust them to new data distributions. The common practice leverages incremental learning (IL), e.g., Cl…

cs.LG2022★ 4 cited

FairNeuron: Improving Deep Neural Network Fairness with Adversary Games on Selective Neurons

Xuanqi Gao, Juan Zhai, Shiqing Ma +3

With Deep Neural Network (DNN) being integrated into a growing number of critical systems with far-reaching impacts on society, there are increasing concerns on their ethical perfo…

cs.CR2021★ 4 cited

Property Inference Attacks Against GANs

Junhao Zhou, Yufei Chen, Chao Shen +1

While machine learning (ML) has made tremendous progress during the past decade, recent research has shown that ML models are vulnerable to various security and privacy attacks. So…

cs.LG2020★ 3 cited

Can We Mitigate Backdoor Attack Using Adversarial Detection Methods?

Kaidi Jin, Tianwei Zhang, Chao Shen +4

Deep Neural Networks are well known to be vulnerable to adversarial attacks and backdoor attacks, where minor modifications on the input are able to mislead the models to give wron…