1 citations · 1 across the 1 of their papers we have counts for
2 papers
cs.LG2021★ 1 cited
A Novel Perspective for Positive-Unlabeled Learning via Noisy Labels
Daiki Tanaka, Daiki Ikami, Kiyoharu Aizawa
Positive-unlabeled learning refers to the process of training a binary classifier using only positive and unlabeled data. Although unlabeled data can contain positive data, all unl…
cs.CV2018
Joint Optimization Framework for Learning with Noisy Labels
Daiki Tanaka, Daiki Ikami, Toshihiko Yamasaki +1
Deep neural networks (DNNs) trained on large-scale datasets have exhibited significant performance in image classification. Many large-scale datasets are collected from websites, h…