Feb 22, 2019 · In this paper, we propose a novel method named active transfer learning (ATL) to solve the above problem.
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Jan 10, 2020 · This article covers three variations of Active Transfer Learning, the simplest being a binary “correct/incorrect” task to predict where a model might make ...
Transfer learning algorithms are used when one has sufficient training data for one supervised learning task (the source task) but only very limited ...
Abstract. We examine activity recognition from accelerometers, which provides at least two major challenges for machine learning. Firstly, the.
This paper proposes an active transfer learning framework by integrating active generation of labelled data and the processing of relevant data.
Nov 8, 2023 · We present our approach combining Active Learning (AL) and Transfer Learning (TL) to adapt HP estimators to individual video domains efficiently.
How can we reuse existing knowledge, in the form of available datasets, when solving a new and apparently un- related target task from a set of unlabeled ...
TL is an area of ML that focuses on utilizing knowledge gained while solving an ML problem and applying the same knowledge to a different but related problem.
Mar 22, 2023 · In this paper, the combination of active and transfer learning was examined with the purpose of developing an effective text categorization ...
Jul 3, 2024 · We proposed a data-efficient active transfer learning (ATL) framework to improve the performance of personal comfort models under limited data.