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A multi-stage data collection strategy using uniform design based sequential designs
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DOI：10.1007/s11222-026-10860-6.png)
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Abstract
En 中文
Recent advances in artificial intelligence technology have brought increasing attention to data collection methods. When prior information is unavailable, space-filling designs offer a robust approach to initial data collection. Traditional space-filling designs distribute points uniformly across the entire design space but often fail to account for variations between subregions. To address this limitation, we propose a multi-stage data collection approach, called the uniform design based sequential design method, which iteratively adds a local uniform design for a subregion at each experimental stage. We also introduce a novel criterion for evaluating the importance of a subregion. Theoretical results and simulations validate the effectiveness of the proposed method, and an application to a high-dimensional image recognition task demonstrates its practical utility.
Keywords:
Integral estimation
Model-free design
Regression tree
Response-driven approach
Space-filling design
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1.6
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175
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0
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