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Random matrices in data analysis

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2004) 3202 6-7
DOI: 10.1007/978-3-540-30116-5_1
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Abstract

We show how carefully crafted random matrices can achieve distance-preserving dimensionality reduction, accelerate spectral computations, and reduce the sample complexity of certain kernel methods.

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Achlioptas, D. (2004). Random matrices in data analysis. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3202, 6–7. https://doi.org/10.1007/978-3-540-30116-5_1

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