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Compressive independent component analysis: theory and algorithms
2022
Information and Inference A Journal of the IMA
Compressive learning forms the exciting intersection between compressed sensing and statistical learning where one exploits sparsity of the learning model to reduce the memory and/or computational complexity of the algorithms used to solve the learning task. In this paper, we look at the independent component analysis (ICA) model through the compressive learning lens. In particular, we show that solutions to the cumulant-based ICA model have a particular structure that induces a low-dimensional
doi:10.1093/imaiai/iaac016
fatcat:rh2l4hgytfaxxnyvpazm5qx4fq