64 citations · 429 across the 97 of their papers we have counts for
4 papers · 2 filters
Stable Prediction via Leveraging Seed Variable
Kun Kuang, Bo Li, Peng Cui +4
In this paper, we focus on the problem of stable prediction across unknown test data, where the test distribution is agnostic and might be totally different from the training one.…
Balance-Subsampled Stable Prediction
Kun Kuang, Hengtao Zhang, Fei Wu +2
In machine learning, it is commonly assumed that training and test data share the same population distribution. However, this assumption is often violated in practice because the s…
Algorithmic Decision Making with Conditional Fairness
Renzhe Xu, Peng Cui, Kun Kuang +4
Nowadays fairness issues have raised great concerns in decision-making systems. Various fairness notions have been proposed to measure the degree to which an algorithm is unfair. I…
Stable Adversarial Learning under Distributional Shifts
Jiashuo Liu, Zheyan Shen, Peng Cui +4
Machine learning algorithms with empirical risk minimization are vulnerable under distributional shifts due to the greedy adoption of all the correlations found in training data. R…