1 citations · 2 across the 5 of their papers we have counts for
3 papers
cs.CV2024
APPLE: Adversarial Privacy-aware Perturbations on Latent Embedding for Unfairness Mitigation
Zikang Xu, Fenghe Tang, Quan Quan +2
Ensuring fairness in deep-learning-based segmentors is crucial for health equity. Much effort has been dedicated to mitigating unfairness in the training datasets or procedures. Ho…
econ.EM2023★ 1 cited
Stochastic Learning of Semiparametric Monotone Index Models with Large Sample Size
Qingsong Yao
I study the estimation of semiparametric monotone index models in the scenario where the number of observation points is extremely large and conventional approaches fail to wor…
cs.CV2023★ 1 cited
Unsupervised augmentation optimization for few-shot medical image segmentation
Quan Quan, Shang Zhao, Qingsong Yao +2
The augmentation parameters matter to few-shot semantic segmentation since they directly affect the training outcome by feeding the networks with varying perturbated samples. Howev…