Isometry pursuit
Fuente:
arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
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| _version_ | 1866918527014797312 |
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| author | Koelle, Samson Meila, Marina |
| author_facet | Koelle, Samson Meila, Marina |
| contents | Isometry pursuit is a convex algorithm for identifying orthonormal column-submatrices of wide matrices. It consists of a novel normalization method followed by multitask basis pursuit. Applied to Jacobians of putative coordinate functions, it helps identity isometric embeddings from within interpretable dictionaries. We provide theoretical and experimental results justifying this method. For problems involving coordinate selection and diversification, it offers a synergistic alternative to greedy and brute force search. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_18502 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Isometry pursuit Koelle, Samson Meila, Marina Machine Learning Artificial Intelligence Information Retrieval Methodology Isometry pursuit is a convex algorithm for identifying orthonormal column-submatrices of wide matrices. It consists of a novel normalization method followed by multitask basis pursuit. Applied to Jacobians of putative coordinate functions, it helps identity isometric embeddings from within interpretable dictionaries. We provide theoretical and experimental results justifying this method. For problems involving coordinate selection and diversification, it offers a synergistic alternative to greedy and brute force search. |
| title | Isometry pursuit |
| topic | Machine Learning Artificial Intelligence Information Retrieval Methodology |
| url | https://arxiv.org/abs/2411.18502 |