1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.CV2024
Learning with Instance-Dependent Noisy Labels by Anchor Hallucination and Hard Sample Label Correction
Po-Hsuan Huang, Chia-Ching Lin, Chih-Fan Hsu +2
Learning from noisy-labeled data is crucial for real-world applications. Traditional Noisy-Label Learning (NLL) methods categorize training data into clean and noisy sets based on…
cs.LG2024★ 1 cited
A Comprehensive Review of Machine Learning Advances on Data Change: A Cross-Field Perspective
Jeng-Lin Li, Chih-Fan Hsu, Ming-Ching Chang +1
Recent artificial intelligence (AI) technologies show remarkable evolution in various academic fields and industries. However, in the real world, dynamic data lead to principal cha…