AI RESEARCH
A Universal Nearest-Neighbor Estimator for Intrinsic Dimensionality
arXiv CS.LG
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ArXi:2603.10493v1 Announce Type: new Estimating the intrinsic dimensionality (ID) of data is a fundamental problem in machine learning and computer vision, providing insight into the true degrees of freedom underlying high-dimensional observations. Existing methods often rely on geometric or distributional assumptions and can significantly fail when these assumptions are violated. In this paper, we