Max filtering with reflection groups
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Abstract (arXiv)
Given a finite-dimensional real inner product space V and a finite subgroup G of linear isometries, max filtering affords a bilipschitz Euclidean embedding of the orbit space V/G. We identify the max filtering maps of minimum distortion in the setting where G is a reflection group. Our analysis involves an interplay between Coxeter's classification and semidefinite programming.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 9 Dec 2022.
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Citing papers per year: 2025: 2; 2026: 2.
4 papers.
- 2025Quantitative Bounds for Sorting-Based Permutation-Invariant Embeddingscited by 2
- 2026Quantitative Approximation Rates for Group Equivariant Learningcited by 1
- 2025If you can distinguish, you can express: Galois theory, Stone--Weierstrass, machine learning, and linguisticscited by 0
- 2026Transversal Pooling Neural Networkscited by 0
- 2026Transversal Pooling Neural Networks28 Sep 2026
- 2026Quantitative Approximation Rates for Group Equivariant Learning23 Feb 2026
- 2025Quantitative Bounds for Sorting-Based Permutation-Invariant Embeddings25 Oct 2025
- 2025If you can distinguish, you can express: Galois theory, Stone--Weierstrass, machine learning, and linguistics10 Oct 2025