Results 101 to 110 of about 8,161,576 (257)
Transfer Learning Approach for Detecting Psychological Distress in Brexit Tweets [PDF]
, 2021 In 2016, United Kingdom (UK) citizens voted to leave the European Union (EU), which was officially implemented in 2020. During this period, UK residents experienced a great deal of uncertainty around the UK’s continued relationship with the EU.
Adedoyin-Olowe, Mariam +3 more
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Learning Transfer: The Missing Link to Learning among School Leaders in Burkina Faso and Ghana
Frontiers in Education, 2018 Every year, billions of dollars are spent on development aid and training around the world. However, only 10% of this training results in the transfer of knowledge, skills, or behaviors learned in the training to the work place.
Corinne Brion, Paula A. Cordeiro
doaj +1 more source
Transfer Learning and Applications [PDF]
, 2012 In machine learning and data mining, we often encounter situations where we have an insufficient amount of high-quality data in a target domain, but we may have plenty of auxiliary data in related domains. Transfer learning aims to exploit these additional data to improve the learning performance in the target domain.
openaire +2 more sources
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Digital technologies hold promise for transforming healthcare by enhancing personalized treatments and offer valuable opportunities to improve patient care. Here, we evaluated several novel, self‐administered, home‐based, digital endpoints for their association with corresponding conventional standard clinical measures (primary) in ...
Arne Mueller +14 more
wiley +1 more source
Transfer, transitions and transformations of learning
, 2013 This book explores one of the enduring issues in educational research and one of the challenges for formal education. That is, understanding the relationship between learning in one context, setting or time and a subsequent related learning experience or
Baartman, L., Middleton, Howard
core
, 2023 reservedIn the recent years Transfer Learning approaches have been widely implemented in several machine learning fields, such as Computer Vision, Natural Language Processing and Time Series Forecasting.
PIVATO, DAVIDE
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Scientific ReportsData sparseness is a major limiting factor for deep machine learning. In the natural sciences, data distributions are heterogeneous. For instance, in chemistry and early-phase drug discovery, compound and molecular property data are typically sparse ...
Antonia Mera +2 more
doaj +1 more source
A Two‐Stage Questionnaire and Actigraphy Screening for iRBD in a Multicenter Retrospective Cohort
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Isolated rapid‐eye‐movement sleep behavior disorder is a prodromal marker of synucleinopathies. However, most cases remain undiagnosed due to the insufficient predictive value of questionnaires and limited access to confirmatory video‐polysomnography. We assessed a two‐stage screening strategy combining a brief questionnaire on rapid‐
Caleb A. Massimi +17 more
wiley +1 more source
Inductive transfer for learning Bayesian networks
, 2010 In several domains it is common to have data from different, but closely related problems. For instance, in manufacturing, many products follow the same industrial process but with different conditions; or in industrial diagnosis, where there is ...
LUIS ENRIQUE SUCAR SUCCAR +2 more
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Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To determine whether myelin‐sensitive quantitative MRI reveals microstructural abnormalities in normal‐appearing cortex (NACtx) in myelin oligodendrocyte glycoprotein antibody–associated disease (MOGAD), indicating that conventional MRI underestimates remission residual cortical injury.
Valentina Camera +20 more
wiley +1 more source