3 citations · 3 across the 10 of their papers we have counts for
4 papers · 1 filter
Differentially Private Conformal Prediction
Jiamei Wu, Ce Zhang, Zhipeng Cai +4
Conformal prediction (CP) has attracted broad attention as a simple and flexible framework for uncertainty quantification through prediction sets. In this work, we study how to dep…
Understanding Fairness and Prediction Error through Subspace Decomposition and Influence Analysis
Enze Shi, Pankaj Bhagwat, Zhixian Yang +2
Machine learning models have achieved widespread success but often inherit and amplify historical biases, resulting in unfair outcomes. Traditional fairness methods typically impos…
Deep Fair Learning: Task-Aware Fair Representations via Joint Distance-Covariance Regularization
Enze Shi, Linglong Kong, Yiqun Xiao +1
Ensuring fairness is essential as machine learning increasingly informs consequential decisions. However, many fairness-aware methods focus on the outputs of individual predictors,…
Online federated learning framework for classification
Wenxing Guo, Jinhan Xie, Jianya Lu +3
In this paper, we develop a novel online federated learning framework for classification, designed to handle streaming data from multiple clients while ensuring data privacy and co…