Results 11 to 20 of about 1,961,679 (175)
Information-theoretic analysis for transfer learning [PDF]
, 2020 Transfer learning, or domain adaptation, is concerned with machine learning problems in which training and testing data come from possibly different distributions (denoted as $\mu$ and $\mu'$, respectively). In this work, we give an information-theoretic
Aickelin, Uwe +3 more
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Expert Systems with Applications, 2010 Transfer learning is a method which aims to improve ''related'' tasks performance. Transfer learning tries to use information gained from related tasks solutions to improve performance of learning strategy. Transfer learning addresses the problem of how to utilize plenty of labeled data in a source domain to solve related but different problems in a ...
Koçer, Barış, Arslan, Ahmet
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Inteligencia Artificial, 2022 Deep Learning and transfer learning models are being used to generate time series forecasts; however, there is scarce evidence about their performance prediction that it is more evident for monthly time series.
Martín Solís +1 more
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Quantum deep transfer learning
New Journal of Physics, 2021 Quantum machine learning (QML) has aroused great interest because it has the potential to speed up the established classical machine learning processes.
Longhan Wang, Yifan Sun, Xiangdong Zhang
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Transfer Learning in Magnetic Resonance Brain Imaging: A Systematic Review
Journal of Imaging, 2021 (1) Background: Transfer learning refers to machine learning techniques that focus on acquiring knowledge from related tasks to improve generalization in the tasks of interest.
Juan Miguel Valverde +6 more
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Factors influencing the learning transfer of nursing students in a non-face-to-face educational environment during the COVID-19 pandemic in Korea: a cross-sectional study using structural equation modeling [PDF]
Journal of Educational Evaluation for Health Professions, 2023 Purpose The aim of this study was to identify factors influencing the learning transfer of nursing students in a non-face-to-face educational environment through structural equation modeling and suggest ways to improve the transfer of learning.
Geun Myun Kim +2 more
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Artificial Intelligence, 2014 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
ZHAO, Peilin +3 more
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Komputika, 2023 Deep learning is a branch of machine learning with many highly successful applications. One application of deep learning is image classification using the Convolutional Neural Network (CNN) algorithm. Large image data is required to classify images with
Muhammad Daffa Arviano Putra +4 more
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Fuzzy Inference and Manifold Regularization Combined Feature Transfer Learning
Jisuanji kexue yu tansuo, 2020 Transfer learning leverages the rich data in the source domain to provide support for building accurate models in the target domain. Feature transfer learning is a kind of widely studied technology in transfer learning, but the existing feature transfer ...
SONG Yixuan, DENG Zhaohong, QIN Bin
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Accounting students' expectations and transition experiences of supervised work experience [PDF]
, 2010 Political and economic discourses position employability as a responsibility of higher education, which utilise mechanisms such as supervised work experience (SWE) to embed employability into the undergraduate curriculum. However, sparse investigation of
Brown M. +17 more
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