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09/10/2023
Outlier Robust Adversarial Training
Supervised learning models are challenged by the intrinsic complexities ...
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06/29/2023
Improving Fairness in Deepfake Detection
Despite the development of effective deepfake detection models in recent...
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11/18/2022
Distributionally Robust Survival Analysis: A Novel Fairness Loss Without Demographics
We propose a general approach for training survival analysis models that...
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07/18/2022
Rank-based Decomposable Losses in Machine Learning: A Survey
Recent works have revealed an essential paradigm in designing loss funct...
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01/22/2022
Differentially Private SGDA for Minimax Problems
Stochastic gradient descent ascent (SGDA) and its variants have been the...
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07/31/2021
T_kML-AP: Adversarial Attacks to Top-k Multi-Label Learning
Top-k multi-label learning, which returns the top-k predicted labels fro...
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06/07/2021
Sum of Ranked Range Loss for Supervised Learning
In forming learning objectives, one oftentimes needs to aggregate a set ...
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10/24/2020
Uncertainty Aware Semi-Supervised Learning on Graph Data
Thanks to graph neural networks (GNNs), semi-supervised node classificat...
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10/05/2020
Learning by Minimizing the Sum of Ranked Range
In forming learning objectives, one oftentimes needs to aggregate a set ...
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09/24/2020
Exposing GAN-generated Faces Using Inconsistent Corneal Specular Highlights
Sophisticated generative adversary network (GAN) models are now able to ...
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10/11/2015
