3 papers
cs.CV2026
Cross-device Collaborative Test-time Adaptation with Zeroth-order Optimization and Model Merging
Yu Mitsuzumi, Akisato Kimura, Yasuhiro Fujiwara +1
Test-time adaptation (TTA) mitigates domain shifts by using incoming test data to update a model on the fly. The majority of TTA methods require resource-intensive backpropagation…
cs.LG2025
Meta-learning Representations for Learning from Multiple Annotators
Atsutoshi Kumagai, Tomoharu Iwata, Taishi Nishiyama +2
We propose a meta-learning method for learning from multiple noisy annotators. In many applications such as crowdsourcing services, labels for supervised learning are given by mult…
cs.LG2024
Meta-learning for Positive-unlabeled Classification
Atsutoshi Kumagai, Tomoharu Iwata, Yasuhiro Fujiwara
We propose a meta-learning method for positive and unlabeled (PU) classification, which improves the performance of binary classifiers obtained from only PU data in unseen target t…