PSPU: Enhanced Positive and Unlabeled Learning by Leveraging Pseudo Supervision
C Wang, C Xu, Z Gan, J Hu, W Zhu, L Ma - arXiv preprint arXiv:2407.06698, 2024 - arxiv.org
Positive and Unlabeled (PU) learning, a binary classification model trained with only positive
and unlabeled data, generally suffers from overfitted risk estimation due to inconsistent data …
and unlabeled data, generally suffers from overfitted risk estimation due to inconsistent data …
PUAL: A Classifier on Trifurcate Positive-Unlabeled Data
Positive-unlabeled (PU) learning aims to train a classifier using the data containing only
labeled-positive instances and unlabeled instances. However, existing PU learning methods …
labeled-positive instances and unlabeled instances. However, existing PU learning methods …
Human-Aligned Topic Model for Explanations of Image Classification
J Yan, S Yamada - 人工知能学会全国大会論文集第38 回(2024), 2024 - jstage.jst.go.jp
Despite significant research efforts to integrate human judgment to improve model
interpretability, there is a continued need to enhance the efficiency of evaluation algorithms …
interpretability, there is a continued need to enhance the efficiency of evaluation algorithms …