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2007 NeurIPS NeurIPS 2007

Learning the structure of manifolds using random projections

Abstract

We present a simple variant of the k-d tree which automatically adapts to intrinsic low dimensional structure in data.

🌉 Interdisciplinary Bridge - Artificial Intelligence and Computer Science and Mathematics & Optimization

📈 Trend Setter - Geometry

🐣 Hot Topic Early Bird - manifold learning

Authors

Yoav Freund, Sanjoy Dasgupta, Mayank Kabra, Nakul Verma

Topics

Machine Learning > Core Methods > Clustering Machine Learning > Core Methods > Representation Learning Machine Learning > Core Methods > Embedding Learning Mathematics & Optimization > Mathematics > Geometry Computer Science > Foundations > Data Structures Machine Learning > Core Methods > Dimensionality Reduction Machine Learning > Core Methods > Feature Learning

Keywords

dimensionality reduction feature learning manifold learning intrinsic dimension k-d tree manifold structure intrinsic dimensionality adaptive k-d tree low-dimensional structure random projection

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