Isometry Pursuit

Abstract

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.

Cite

Text

Koelle and Meila. "Isometry Pursuit." NeurIPS 2024 Workshops: InterpretableAI, 2024.

Markdown

[Koelle and Meila. "Isometry Pursuit." NeurIPS 2024 Workshops: InterpretableAI, 2024.](https://mlanthology.org/neuripsw/2024/koelle2024neuripsw-isometry/)

BibTeX

@inproceedings{koelle2024neuripsw-isometry,
  title     = {{Isometry Pursuit}},
  author    = {Koelle, Samson J and Meila, Marina},
  booktitle = {NeurIPS 2024 Workshops: InterpretableAI},
  year      = {2024},
  url       = {https://mlanthology.org/neuripsw/2024/koelle2024neuripsw-isometry/}
}