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Experiential Learning
Known as:
Active learning
, Learning, Active
, Learning, Experiential
National Institutes of Health
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Problem-Based Learning
Papers overview
Semantic Scholar uses AI to extract papers important to this topic.
2019
2019
ALiPy: Active Learning in Python
Ying-Peng Tang
,
Guo-Xiang Li
,
Sheng-Jun Huang
arXiv.org
2019
Corpus ID: 58004669
Supervised machine learning methods usually require a large set of labeled examples for model training. However, in many real…
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Review
2018
Review
2018
Optimizing spectroscopic follow-up strategies for supernova photometric classification with active learning
E. O. Ishida
,
R. Beck
,
+11 authors
E. Gangler
Monthly notices of the Royal Astronomical Society
2018
Corpus ID: 119346264
We report a framework for spectroscopic follow-up design for optimizing supernova photometric classification. The strategy…
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Review
2017
Review
2017
Machine learning for epigenetics and future medical applications
Lawrence Holder
,
M. Haque
,
M. K. Skinner
Epigenetics
2017
Corpus ID: 20916704
ABSTRACT Understanding epigenetic processes holds immense promise for medical applications. Advances in Machine Learning (ML) are…
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Highly Cited
2017
Highly Cited
2017
Flipping around the classroom: Accelerated Bachelor of Science in Nursing students' satisfaction and achievement.
Majeda M. El-Banna
,
M. Whitlow
,
A. McNelis
Nurse Education Today
2017
Corpus ID: 23772077
Review
2017
Review
2017
Video Coaching as an Efficient Teaching Method for Surgical Residents-A Randomized Controlled Trial.
M. Soucisse
,
K. Boulva
,
L. Sidéris
,
P. Drolet
,
M. Morin
,
P. Dubé
Journal of Surgical Education
2017
Corpus ID: 2928826
Highly Cited
2016
Highly Cited
2016
An Active Learning Framework for Hyperspectral Image Classification Using Hierarchical Segmentation
Zhou Zhang
,
Edoardo Pasolli
,
M. Crawford
,
J. Tilton
IEEE Journal of Selected Topics in Applied Earth…
2016
Corpus ID: 39403764
Augmenting spectral data with spatial information for image classification has recently gained significant attention, as…
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Highly Cited
2015
Highly Cited
2015
A Joint Gaussian Process Model for Active Visual Recognition with Expertise Estimation in Crowdsourcing
Chengjiang Long
,
G. Hua
,
Ashish Kapoor
International Journal of Computer Vision
2015
Corpus ID: 6144515
We present a noise resilient probabilistic model for active learning of a Gaussian process classifier from crowds, i.e., a set of…
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Review
2013
Review
2013
Applying active learning to high-throughput phenotyping algorithms for electronic health records data.
Yukun Chen
,
R. Carroll
,
+4 authors
Hua Xu
JAMIA Journal of the American Medical Informatics…
2013
Corpus ID: 9402907
OBJECTIVES Generalizable, high-throughput phenotyping methods based on supervised machine learning (ML) algorithms could…
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Review
2010
Review
2010
Comparing Team-Based and Mixed Active-Learning Methods in an Ambulatory Care Elective Course
Michelle M. Zingone
,
A. Franks
,
Alexander B. Guirguis
,
Christa M. George
,
Amanda Howard-Thompson
,
R. Heidel
American Journal of Pharmaceutical Education
2010
Corpus ID: 6782365
Objectives. To assess students' performance and perceptions of team-based and mixed active-learning methods in 2 ambulatory care…
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Highly Cited
2003
Highly Cited
2003
Reclaiming and re-embodying experiential learning through complexity science
T. Fenwick
2003
Corpus ID: 18912761
Abstract At a time when ‘informal’ and ‘practice-based’ learning are receiving unprecedented emphasis in lifelong learning…
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