4 citations · 15 across the 11 of their papers we have counts for
5 papers · 1 filter
Classification-Head Bias in Class-Level Machine Unlearning: Diagnosis, Mitigation, and Evaluation
Weidong Zheng, Kongyang Chen, Yuanwei Guo +1
Class-level machine unlearning aims to remove the influence of specified classes while preserving model utility on retained classes. Existing methods are commonly evaluated by reta…
Temporal-Decay Shapley: A Time-Aware Data Valuation Framework for Time-Series Data
Chuwen Pang, Bing Mi, Kongyang Chen
With the rapid development of machine learning applications on time-series data, accurately assessing the value of training samples has become essential for data selection, noise d…
Federated Learning for Data Market: Shapley-UCB for Seller Selection and Incentives
Kongyang Chen, Zeming Xu
In recent years, research on the data trading market has been continuously deepened. In the transaction process, there is an information asymmetry process between agents and seller…
Machine Unlearning in Contrastive Learning
Zixin Wang, Kongyang Chen
Machine unlearning is a complex process that necessitates the model to diminish the influence of the training data while keeping the loss of accuracy to a minimum. Despite the nume…
Federated Unlearning for Human Activity Recognition
Kongyang Chen, Dongping zhang, Yaping Chai +3
The rapid evolution of Internet of Things (IoT) technology has spurred the widespread adoption of Human Activity Recognition (HAR) in various daily life domains. Federated Learning…