Results 11 to 20 of about 8,161,576 (257)
A Proposal of Transfer Learning for Monthly Macroeconomic Time Series Forecast
Engineering Proceedings, 2023 Transfer learning has not been widely explored with time series. However, it could boost the application and performance of deep learning models for predicting macroeconomic time series with few observations, like monthly variables.
Martín Solís +1 more
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wassermanlab/TF-Binding-Transfer-Learning: Transfer learning publication
, 2021 Code used to generate the results for the publication "Biologically-relevant transfer learning improves transcription factor binding prediction"
Oriol Fornes
core +1 more source
Learning to Transfer Learn: Reinforcement Learning-Based Selection for Adaptive Transfer Learning [PDF]
, 2020 We propose a novel adaptive transfer learning framework, learning to transfer learn (L2TL), to improve performance on a target dataset by careful extraction of the related information from a source dataset. Our framework considers cooperative optimization of shared weights between models for source and target tasks, and adjusts the constituent loss ...
Linchao Zhu +3 more
openaire +2 more sources
Transfer, Learning, and Innovation: Perspectives Informed by Occupational Practices
, 2021 The process of thinking and acting often referred to as transfer in the educational literature is positioned as being a key problem to be addressed educationally.
Billett, Stephen, Stephen Billett
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Faculty and Student Attitudes about Transfer of Learning [PDF]
InSight, 2008 Transfer of learning is using previous knowledge in novel contexts. While this is a basic assumption of the educational process, students may not always perceive all the options for using what they have learned in different, novel situations. Within the
Robin Lightner, PhD +2 more
doaj +6 more sources
Electroencephalogram-Based Preference Prediction Using Deep Transfer Learning
IEEE Access, 2020 Transfer learning is an approach in machine learning where a model that was built and trained on one task is re-purposed on a second task. The success of transfer learning in computer vision has motivated its use in neuroscience. Although common in image
Mashael S. Aldayel +2 more
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Quantum Adversarial Transfer Learning
Entropy, 2023 Adversarial transfer learning is a machine learning method that employs an adversarial training process to learn the datasets of different domains. Recently, this method has attracted attention because it can efficiently decouple the requirements of ...
Longhan Wang, Yifan Sun, Xiangdong Zhang
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Frontiers in Psychology, 2018 Introduction: Consolidation is defined as the time necessary for memory stabilization after learning. In the present study we focused on effects of interference during the first 12 consolidation minutes after learning.
Zrinka Sosic-Vasic +7 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
doaj +1 more source