Isometry pursuit

Samson J Koelle, Marina Meila

Keywords: Sparse coding, interpretable dictionaries, manifold learning

TL;DR: Isometry pursuit is an efficient algorithm for selecting features from within a dictionary

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.

Track: Main track

Submitted Paper: No

Published Paper: No

Submission Number: 56