The challenge of machine learning in space weather: Nowcasting and forecasting

E Camporeale - Space weather, 2019 - Wiley Online Library
The numerous recent breakthroughs in machine learning make imperative to carefully
ponder how the scientific community can benefit from a technology that, although not …

Improving refugee integration through data-driven algorithmic assignment

K Bansak, J Ferwerda, J Hainmueller, A Dillon… - Science, 2018 - science.org
Developed democracies are settling an increased number of refugees, many of whom face
challenges integrating into host societies. We developed a flexible data-driven algorithm that …

[HTML][HTML] Using artificial intelligence to improve real-time decision-making for high-impact weather

A McGovern, KL Elmore, DJ Gagne… - Bulletin of the …, 2017 - journals.ametsoc.org
Using Artificial Intelligence to Improve Real-Time Decision-Making for High-Impact Weather
in: Bulletin of the American Meteorological Society Volume 98 Issue 10 (2017) Jump to …

Real-time scene text localization and recognition

L Neumann, J Matas - 2012 IEEE conference on computer …, 2012 - ieeexplore.ieee.org
An end-to-end real-time scene text localization and recognition method is presented. The
real-time performance is achieved by posing the character detection problem as an efficient …

Prediction of students' early dropout based on their interaction logs in online learning environment

AA Mubarak, H Cao, W Zhang - Interactive Learning Environments, 2022 - Taylor & Francis
Online learning has become more popular in higher education since it adds convenience
and flexibility to students' schedule. But, it has faced difficulties in the retention of the …

Predicting good probabilities with supervised learning

A Niculescu-Mizil, R Caruana - … of the 22nd international conference on …, 2005 - dl.acm.org
We examine the relationship between the predictions made by different learning algorithms
and true posterior probabilities. We show that maximum margin methods such as boosted …

A machine-learning approach to predicting Africa's electricity mix based on planned power plants and their chances of success

G Alova, PA Trotter, A Money - Nature Energy, 2021 - nature.com
Energy scenarios, relying on wide-ranging assumptions about the future, do not always
adequately reflect the lock-in risks caused by planned power-generation projects and the …

Identifying at-risk students in massive open online courses

J He, J Bailey, B Rubinstein, R Zhang - Proceedings of the AAAI …, 2015 - ojs.aaai.org
Abstract Massive Open Online Courses (MOOCs) have received widespread attention for
their potential to scale higher education, with multiple platforms such as Coursera, edX and …

A machine learning framework to identify students at risk of adverse academic outcomes

H Lakkaraju, E Aguiar, C Shan, D Miller… - Proceedings of the 21th …, 2015 - dl.acm.org
Many school districts have developed successful intervention programs to help students
graduate high school on time. However, identifying and prioritizing students who need those …

A unified view of performance metrics: Translating threshold choice into expected classification loss

J Hernández-Orallo, P Flach, C Ferri - The Journal of Machine Learning …, 2012 - dl.acm.org
Many performance metrics have been introduced in the literature for the evaluation of
classification performance, each of them with different origins and areas of application …