A geometric approach to archetypal analysis via Sparse Projections
Archetypal analysis (AA) aims to extract patterns using self-expressive decomposition of data as convex combinations of extremal points (on the convex hull) of the data. This work presents a computationally efficient greedy AA (GAA) algorithm. GAA leverages the underlying geometry and sparseness pro...
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| Format: | Conference item |
| Language: | English |
| Published: |
Proceedings of Machine Learning Research
2020
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