1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.LG2025
Set a Thief to Catch a Thief: Combating Label Noise through Noisy Meta Learning
Hanxuan Wang, Na Lu, Xueying Zhao +4
Learning from noisy labels (LNL) aims to train high-performance deep models using noisy datasets. Meta learning based label correction methods have demonstrated remarkable performa…
cs.LG2024
A Multi-module Robust Method for Transient Stability Assessment against False Label Injection Cyberattacks
Hanxuan Wang, Na Lu, Yinhong Liu +2
The success of deep learning in transient stability assessment (TSA) heavily relies on high-quality training data. However, the label information in TSA datasets is vulnerable to c…
cs.CV2022★ 1 cited
Self-Evolutionary Clustering
Hanxuan Wang, Na Lu, Qinyang Liu
Deep clustering outperforms conventional clustering by mutually promoting representation learning and cluster assignment. However, most existing deep clustering methods suffer from…