advanced-linear-algebra
Low-rank approximation in practice
taught
Truncating a matrix's SVD at a chosen rank compresses it into far fewer numbers while controlling the guaranteed error exactly, via Eckart-Young's own error formula.
Taught in
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Low-rank approximation in practice
Advanced Linear Algebra
Requires
- the-eckart-young-theorem required
Required by
- Image compression required
- PCA is an SVD required
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