Results 11 to 20 of about 175,760 (266)
IEEE Access, 2019 Dropout is an effective regularization method for deep learning tasks. Several variants of dropout based on sampling with different distributions have been proposed individually and have shown good generalization performance on various learning tasks ...
Lei Liu +4 more
doaj +2 more sources
Machine Learning, 2022 AbstractDespite of its importance for safe machine learning, uncertainty quantification for neural networks is far from being solved. State-of-the-art approaches to estimate neural uncertainties are often hybrid, combining parametric models with explicit or implicit (dropout-based) ensembling.
Joachim Sicking +5 more
openaire +2 more sources
Avoiding Academic Burnout: Academic Factors That Enhance University Student Engagement
Behavioral Sciences, 2023 Burnout is one of the major problems in higher education and is linked to a decline in students’ academic performance and achievement. Burnout, when prolonged over time and added to stress and high workloads, promotes the intention to drop out of studies,
Salvador Reyes-de-Cózar +2 more
doaj +1 more source
High prevalence and risk factors of dropout intention among Chinese medical postgraduates
Medical Education Online, 2022 Background A high attrition rate in medical students has exacerbated the physician shortage in China. However, few studies have explored the risk factors of dropout intention in medical postgraduates.
Pu Peng +22 more
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Early Indicators of Student Success
Journal of Postsecondary Student Success, 2022 This paper reports the results of a four-state collaboration––Texas, New York, Virginia, and Illinois––that uses Student Unit Record Database Systems that track students from high school into college.
Paul Attewell +9 more
doaj +1 more source
International Review of Research in Open and Distributed Learning, 2021 Flexibility is typical of open universities and their e-learning designs. While this constitutes their main attraction, promising learners will be able to study “anytime, anyplace,” this also demands more self-regulation and engagement, a cause for ...
Marlon Xavier, Julio Meneses
doaj +1 more source
Medical prediction from missing data with max-minus negative regularized dropout
Frontiers in Neuroscience, 2023 Missing data is a naturally common problem faced in medical research. Imputation is a widely used technique to alleviate this problem. Unfortunately, the inherent uncertainty of imputation would make the model overfit the observed data distribution ...
Lvhui Hu +3 more
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Student Dropout Prediction [PDF]
, 2020 Among the many open problems in the learning process, students dropout is one of the most complicated and negative ones, both for the student and the institutions, and being able to predict it could help to alleviate its social and economic costs. To address this problem we developed a tool that, by exploiting machine learning techniques, allows to ...
Del Bonifro F. +3 more
openaire +3 more sources
Novel Deep Convolutional Neural Network-Based Contextual Recognition of Arabic Handwritten Scripts
Entropy, 2021 Offline Arabic Handwriting Recognition (OAHR) has recently become instrumental in the areas of pattern recognition and image processing due to its application in several fields, such as office automation and document processing.
Rami Ahmed +7 more
doaj +1 more source