41 citations · 47 across the 8 of their papers we have counts for
4 papers
Enhancing Label Sharing Efficiency in Complementary-Label Learning with Label Augmentation
Wei-I Lin, Gang Niu, Hsuan-Tien Lin +1
Complementary-label Learning (CLL) is a form of weakly supervised learning that trains an ordinary classifier using only complementary labels, which are the classes that certain in…
Semi-Supervised Domain Adaptation with Source Label Adaptation
Yu-Chu Yu, Hsuan-Tien Lin
Semi-Supervised Domain Adaptation (SSDA) involves learning to classify unseen target data with a few labeled and lots of unlabeled target data, along with many labeled source data…
Can Active Learning Experience Be Transferred?
Hong-Min Chu, Hsuan-Tien Lin
Active learning is an important machine learning problem in reducing the human labeling effort. Current active learning strategies are designed from human knowledge, and are applie…
An Online Boosting Algorithm with Theoretical Justifications
Shang-Tse Chen, Hsuan-Tien Lin, Chi-Jen Lu
We study the task of online boosting--combining online weak learners into an online strong learner. While batch boosting has a sound theoretical foundation, online boosting deserve…