Dimensionality reduction

Kent Quanrud · 75:14

This lecture proves the Johnson–Lindenstrauss fact that n vectors in arbitrarily high dimension can be mapped by a random Gaussian matrix into about log n / ε² dimensions while preserving all pairwise Euclidean distan...

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