Nearly optimal linear embeddings into very low dimensions
We propose algorithms for constructing linear embeddings of a finite dataset V ⊂ ℝ[superscript d] into a k-dimensional subspace with provable, nearly optimal distortions. First, we propose an exhaustive-search-based algorithm that yields a k-dimensional linear embedding with distortion at most ε[sub...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Institute of Electrical and Electronics Engineers (IEEE)
2018
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| Online Access: | http://hdl.handle.net/1721.1/113673 https://orcid.org/0000-0002-7983-9524 |