Principal component analysis by optimisation of symmetric functions has no spurious local optima
Principal component analysis (PCA) finds the best linear representation of data and is an indispensable tool in many learning and inference tasks. Classically, principal components of a dataset are interpreted as the directions that preserve most of its “energy,” an interpretation that is theoretica...
| Main Authors: | , |
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| Format: | Journal article |
| Language: | English |
| Published: |
Society for Industrial and Applied Mathematics
2020
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