Mar 9, 2017 � In this paper, we suggest a novel data-driven approach to active learning (AL). The key idea is to train a regressor that predicts the expected error reduction.
In this paper, we suggest a novel data-driven approach to active learning (AL). The key idea is to train a regressor that predicts the expected error�...
In this paper, we suggest a novel data-driven approach to active learning (AL). The key idea is to train a regressor that predicts the expected error�...
Aug 2, 2023 � Active learning is a special case of machine learning in which a learning algorithm can interactively query a user (or some other information source) to label�...
This project contains code for paper Ksenia Konyushkova, Raphael Sznitman, Pascal Fua 'Learning Active Learning from Data', NIPS 2017
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Aug 10, 2021 � My question is active learning is not needed anymore ?. I know prodigy that using active learning for labeling data, however I do not know whether active�...
A novel data-driven approach to active learning is suggested to train a regressor that predicts the expected error reduction for a candidate sample in a�...
Jan 11, 2024 � Active learning is a special case of Supervised Machine Learning. This approach is used to construct a high-performance classifier while keeping the size of�...
Active learning is semi-supervised learning with a human-in-the-loop. It can be used to decrease the amount of data that needs to be labeled and can also�...
Active learning is a special case of semi-supervised machine learning in which a learning algorithm is able to interactively.
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