Feb 8, 2024 · This approach facilitates a more accurate estimation of the overall error reduction, without extensive computations or reliance on labeled data.
Oct 9, 2024 · The paper presents Direct Acquisition Optimization (DAO), a novel active learning method that enhances sample selection in low-budget settings.
Feb 8, 2024 · This approach facilitates a more accurate estimation of the overall error reduction, without extensive computations or reliance on labeled data.
Experiments demonstrate the effectiveness of DAO in low-budget settings, outperforming state- of-the-arts approaches across seven benchmarks. 1 Introduction.
Direct Acquisition Optimization for Low-Budget Active Learning. Z Zhao, Y Jiang, Y Chen. arXiv preprint arXiv:2402.06045, 2024. 4, 2024. Model-agnostic meta ...
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Direct Acquisition Optimization for Low-Budget Active Learning · no code implementations • 8 Feb 2024 • Zhuokai Zhao, Yibo Jiang, Yuxin Chen. Active Learning ...
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This paper introduces an integer optimization problem for selecting a core set that minimizes the discrete Wasserstein distance from the unlabeled pool. We ...