Free component analysis: theory, algorithms and applications

DOI10.1007/s10208-022-09564-wzbMath1521.60006arXiv1905.01713OpenAlexW4223598114MaRDI QIDQ6101268

No author found.

Publication date: 20 June 2023

Published in: Foundations of Computational Mathematics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1905.01713

zbMATH Keywords

blind source separationindependent component analysisrandom matricesfree probability

Mathematics Subject Classification ID

Random matrices (probabilistic aspects) (60B20) Computing methodologies for image processing (68U10) Free probability and free operator algebras (46L54)

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Free probability and random matrices
• Source separation using single channel ICA
• Limit laws for random matrices and free products
• The analogues of entropy and of Fisher's information measure in free probability theory. I
• Multiplicative functions on the lattice of non-crossing partitions and free convolution
• Independent component analysis, a new concept?
• The analogues of entropy and of Fisher's information measure in free probability theory. II
• A unifying information-theoretic framework for independent component analysis
• Robust blind source separation algorithms using cumulants.
• Cumulants in noncommutative probability theory. I: Noncommutative exchangeability systems
• Provable ICA with unknown Gaussian noise, and implications for Gaussian mixtures and autoencoders
• Efficient independent component analysis
• Rectangular random matrices, related convolution
• Asymptotically liberating sequences of random unitary matrices
• Manopt, a Matlab toolbox for optimization on manifolds
• Lectures on the Combinatorics of Free Probability
• Random matrix theory
• Derivatives and Perturbations of Eigenvectors
• Independent component analysis applied to feature extraction from colour and stereo images
• Fourth-Order Cumulant-Based Blind Identification of Underdetermined Mixtures
• 10.1162/jmlr.2003.4.7-8.1297
• Traffic Distributions and Independence: Permutation Invariant Random Matrices and the Three Notions of Independence
• Underdetermined blind source separation using sparse representations

This page was built for publication: Free component analysis: theory, algorithms and applications