Discussion of “Independent component analysis by robust distance correlation”: a note on the geometry of the bowl transform and on the reach of the consistency for robust ICA

Abstract This is a discussion of PICARD, the robust independent component analysis (ICA) estimator built on a transformed distance correlation and on the bowl transform.I develop two threads.The first reads the bowl transform as a multivariate redescending $\psi$-function, makes its exponential decay explicit, and describes how the transformed norm concentrates as the dimension grows.The second examines the reach of the strong-consistency result, relating its population target to classical ICA identifiability and to the behavior of robust whitening under non-elliptical sources.

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Publication Details

Journal
Advances in Data Analysis and Classification
Published
2026-06-19
DOI
https://doi.org/10.1007/s11634-026-00696-3
Primary Topic
Blind Source Separation Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Discussion of “Independent component analysis by robust distance correlation”: a note on the geometry of the bowl transform and on the reach of the consistency for robust ICA

Pietro Coretto
Advances in Data Analysis and Classification
Blind Source Separation Techniques
article

Discussion of “Independent component analysis by robust distance correlation”: a note on the geometry of the bowl transform and on the reach of the consistency for robust ICA

Pietro Coretto
article en

Abstract

Abstract This is a discussion of PICARD, the robust independent component analysis (ICA) estimator built on a transformed distance correlation and on the bowl transform.I develop two threads.The first reads the bowl transform as a multivariate redescending $\psi$-function, makes its exponential decay explicit, and describes how the transformed norm concentrates as the dimension grows.The second examines the reach of the strong-consistency result, relating its population target to classical ICA identifiability and to the behavior of robust whitening under non-elliptical sources.

Advances in Data Analysis and Classification
University of Salerno (IT)
Università degli Studi di Salerno
Reduced inequalities
Openalex Percentile: Top 5%
Blind Source Separation Techniques
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