This paper focuses on designing a semi-supervised classifier trained by using unlabeled samples drawn by the same distribution as test samples, and presents a ...
ABSTRACT. The transfer learning problem of designing good classifiers with a high generalization ability by using labeled samples.
A robust semi-supervised classification method for transfer learning ...
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This paper focuses on designing a semi-supervised classifier trained by using unlabeled samples drawn by the same distribution as test samples, and presents a ...
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Nov 6, 2018 · Akinori Fujino, Naonori Ueda, Masaaki Nagata: A robust semi-supervised classification method for transfer learning. CIKM 2010: 379-388.
Jan 15, 2024 · In this paper, we propose an open-world SSL method for Self-learning Open-world Classes (SSOC), which can explicitly self-learn multiple unknown classes.
Jan 29, 2024 · In this paper, we aim to evaluate the performance of a trained binary classifier on unlabeled target population based on ROC analysis.
Mar 29, 2024 · Semi-supervised learning (SSL) is a machine learning technique that uses a small portion of labeled data and lots of unlabeled data to train a predictive model.
Aiming at enabling transfer learning under semi-supervised settings, we propose a hierarchical self-regularization mechanism to exploit unlabeled samples more ...
Missing: robust | Show results with:robust
Oct 31, 2022 · This paper proposes a new SSL approach that can classify not only seen classes but also unseen classes.
GSCCTL: a general semi-supervised scene classification method for ...
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Specifically, the GSCCTL model iterates between (1) scene clustering and (2) transfer learning to improve scene classification performance for the HSI data set.
Missing: robust | Show results with:robust