An Ensemble Transfer Learning Model for Detecting Stego Images
Applied Sciences, 2023 As internet traffic grows daily, so does the need to protect it. Network security protects data from unauthorized access and ensures their confidentiality and integrity.
Dina Yousif Mikhail +2 more
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Student Status Supervision in Ideological and Political Machine Teaching Based on Machine Learning [PDF]
E3S Web of Conferences, 2021 Under the premise of active in the field of machine learning, this paper takes online teaching system of ideological and Political education as an example to study machine learning and machine teaching system.
An Chang
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Integrating Iterative Machine Teaching and Active Learning into the Machine Learning Loop
Procedia Computer Science, 2021 Xunta de Galicia; ED431G 2019 ...
Mosqueira-Rey, Eduardo +2 more
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Calibration of uncertainty in the active learning of machine learning force fields
Machine Learning: Science and Technology, 2023 FFLUX is a machine learning force field that uses the maximum expected prediction error (MEPE) active learning algorithm to improve the efficiency of model training.
Adam Thomas-Mitchell +2 more
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PAL – parallel active learning for machine-learned potentials
Digital DiscoveryAn automated, modular, and parallel active learning (PAL) library that integrates AL tasks and manages their execution and communication on shared- and distributed-memory systems using the Message Passing Interface (MPI).
Chen Zhou +7 more
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Yoked learning in molecular data science
Artificial Intelligence in the Life SciencesActive machine learning is an established and increasingly popular experimental design technique where the machine learning model can request additional data to improve the model's predictive performance. It is generally assumed that this data is optimal
Zhixiong Li +3 more
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Multi-Label Active Learning-Based Machine Learning Model for Heart Disease Prediction
Sensors, 2022 The rapid growth and adaptation of medical information to identify significant health trends and help with timely preventive care have been recent hallmarks of the modern healthcare data system.
Ibrahim M. El-Hasnony +3 more
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Multi-Class Adaptive Active Learning for Predicting Student Anxiety
IEEE AccessThis research delves into applying active and machine learning techniques to predict student anxiety. This research explores how these technologies can be explored to understand and predict student anxiety levels.
Ahmad Almadhor +6 more
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Data leakage detection in machine learning code: transfer learning, active learning, or low-shot prompting? [PDF]
PeerJ Computer ScienceWith the increasing reliance on machine learning (ML) across diverse disciplines, ML code has been subject to a number of issues that impact its quality, such as lack of documentation, algorithmic biases, overfitting, lack of reproducibility, inadequate ...
Nouf Alturayeif, Jameleddine Hassine
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Automated discovery of a robust interatomic potential for aluminum
Nature Communications, 2021 The accuracy of a machine-learned potential is limited by the quality and diversity of the training dataset. Here the authors propose an active learning approach to automatically construct general purpose machine-learning potentials here demonstrated for
Justin S. Smith +10 more
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