no code implementations • 22 Apr 2024 • Yujin Han, Difan Zou
GIC trains a spurious attribute classifier based on two key properties of spurious correlations: (1) high correlation between spurious attributes and true labels, and (2) variability in this correlation between datasets with different group distributions.
no code implementations • 4 Feb 2023 • Yujin Han, Leying Guan
Split learning (splitNN) has emerged as a popular strategy for addressing the high computational costs and low modeling efficiency in Vertical Federated Learning (VFL).
1 code implementation • 4 Feb 2023 • Yujin Han, Mingwenchan Xu, Leying Guan
The Random Forests classifier, a widely utilized off-the-shelf classification tool, assumes training and test samples come from the same distribution as other standard classifiers.
no code implementations • 3 Apr 2022 • Yujin Han, Pan Du, Kai Yang
With the aim of obtaining an outstanding performance with less time cost, we propose a novel model in a vertically federated setting termed as Federated Gradient Boosting Forest (FedGBF).