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Yize Li

3 accepted papers

2025

FairSMOE: Mitigating Multi-Attribute Fairness Problem with Sparse Mixture-of-Experts

IJCAI 2025

Real‐world datasets usually contain multiple attributes, making it essential to ensure fairness across all of them simultaneously. However, different attributes may vary in difficulty, and no existing approaches have effectively addressed this issue. Consequently, an attribute‐adaptive strategy is n

Cited by 0SourcePDFScholar
2025

Pruning then Reweighting: Towards Data-Efficient Training of Diffusion Models

ICASSP 2025accepted

Despite the remarkable generation capabilities of Diffusion Models (DMs), conducting training and inference remains computationally expensive. Previous works have been devoted to accelerating diffusion sampling, but achieving data-efficient diffusion training has often been overlooked. In this work,…

Cited by 0SourceScholar
2022

Reverse Engineering of Imperceptible Adversarial Image Perturbations

ICLR 2022poster

It has been well recognized that neural network based image classifiers are easily fooled by images with tiny perturbations crafted by an adversary. There has been a vast volume of research to generate and defend such adversarial attacks. However, the following problem is left unexplored: How to rev…