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Abstract: In this paper two active learning methods are proposed in the machine learning literature, both of them based on difference calculation idea.
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Abstract—In this paper two active learning methods are proposed in the machine learning literature, both of them based on difference calculation idea.
Instead of pre-clustering the datasets, the algorithm uses this criterion to select examples for active learning classification (Cebron & Berthold, 2009).
Mar 17, 2024 · There are many different query strategies, but they can be broadly classified into two categories: generative models and optimization methods.
Query strategies in active learning refer to methods used to select informative samples to be labeled by a human annotator, with the goal of improving the ...
Active learning is a type of machine learning where a model in production selects samples to send to labellisation on its own.
Oct 9, 2022 · Active learning turns the unfavorable number of unstructured data into an advantage: it's a type of semi-supervised learning where a small set of labeled data ...
Oct 17, 2024 · This work presents the first differentiable AL strategy search method, named AutoAL, which is designed on top of existing AL sampling strategies.
May 22, 2022 · Uncertainty-based query strategies used to be the most common choice in active learning, using uncertainty scores obtained from the learning al ...
Learn about active learning in machine learning to reduce labeling costs and improve model performance. Active learning strategies and applications in ML.