Results 11 to 20 of about 168,521,757 (307)
Transfer Learning and Curriculum Learning in Sokoban [PDF]
, 2022 Transfer learning can speed up training in machine learning and is regularly used in classification tasks. It reuses prior knowledge from other tasks to pre-train networks for new tasks. In reinforcement learning, learning actions for a behavior policy that can be applied to new environments is still a challenge, especially for tasks that involve much ...
Zhao Yang 0003, Mike Preuss, Aske Plaat
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Adaptive Transfer Learning: a simple but effective transfer learning
CoRR, 2021 Transfer learning (TL) leverages previously obtained knowledge to learn new tasks efficiently and has been used to train deep learning (DL) models with limited amount of data. When TL is applied to DL, pretrained (teacher) models are fine-tuned to build domain specific (student) models.
Jung H. Lee +9 more
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When & How to Transfer with Transfer Learning
CoRR, 2022 In deep learning, transfer learning (TL) has become the de facto approach when dealing with image related tasks. Visual features learnt for one task have been shown to be reusable for other tasks, improving performance significantly. By reusing deep representations, TL enables the use of deep models in domains with limited data availability, limited ...
Adrian Tormos +3 more
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Progressive Transfer Learning [PDF]
IEEE Transactions on Image Processing, 2022 10 pages, 4 figures, journel verison of our published short paper on ...
Zhengxu Yu +5 more
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What associative learning in insects tells us about the evolution of learning and fixed behavior [PDF]
, 2015 Contemporary models for the evolution of learning suggest that environmental predictability plays a critical role in whether learning is expected to evolve in a particular species, a claim originally made over 50 years ago.
Hollis, Karen L. +3 more
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The effect of nonlinear pedagogy on the acquisition of game skills in a territorial game
Frontiers in Psychology, 2023 IntroductionNonlinear Pedagogy (NP), underpinned by Ecological Dynamics, provides a suitable pedagogical approach for practitioners (e.g., Physical Educators, coaches) to encourage exploratory learning that is learner-centered even in Traditional ...
Jia Yi Chow +4 more
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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
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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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Education Sciences, 2023 The transfer of learning is arguably the most enduring goal of education. The history of science reveals that although numerous theories have been transferred from the natural sciences to the socio-political realm, educational practitioners have often ...
Chen Chen +4 more
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