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Latent Variable Analysis and Signal Separation [electronic resource] : 14th International Conference, LVA/ICA 2018, Guildford, UK, July 2-5, 2018, Proceedings / edited by Yannick Deville, Sharon Gannot, Russell Mason, Mark D. Plumbley, Dominic Ward.

Contributor(s): Deville, Yannick [editor.] | Gannot, Sharon [editor.] | Mason, Russell [editor.] | Plumbley, Mark D [editor.] | Ward, Dominic [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Theoretical Computer Science and General Issues: 10891Publisher: Cham : Springer International Publishing : Imprint: Springer, 2018Edition: 1st ed. 2018.Description: XVII, 580 p. 150 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319937649.Subject(s): Pattern recognition systems | Computer vision | Artificial intelligence | Computer simulation | Numerical analysis | Computer networks  | Automated Pattern Recognition | Computer Vision | Artificial Intelligence | Computer Modelling | Numerical Analysis | Computer Communication NetworksAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 006.4 Online resources: Click here to access online
Contents:
Structured Tensor Decompositions and Applications -- Matrix and Tensor Factorizations -- ICA Methods -- Nonlinear Mixtures -- Audio Data and Methods -- Signal Separation Evaluation Campaign -- Deep Learning and Data-driven Methods -- Advances in Phase Retrieval and Applications -- Sparsity-Related Methods -- Biomedical Data and Methods.
In: Springer Nature eBookSummary: This book constitutes the proceedings of the 14th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2018, held in Guildford, UK, in July 2018. The 52 full papers were carefully reviewed and selected from 62 initial submissions. As research topics the papers encompass a wide range of general mixtures of latent variables models but also theories and tools drawn from a great variety of disciplines such as structured tensor decompositions and applications; matrix and tensor factorizations; ICA methods; nonlinear mixtures; audio data and methods; signal separation evaluation campaign; deep learning and data-driven methods; advances in phase retrieval and applications; sparsity-related methods; and biomedical data and methods.
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Structured Tensor Decompositions and Applications -- Matrix and Tensor Factorizations -- ICA Methods -- Nonlinear Mixtures -- Audio Data and Methods -- Signal Separation Evaluation Campaign -- Deep Learning and Data-driven Methods -- Advances in Phase Retrieval and Applications -- Sparsity-Related Methods -- Biomedical Data and Methods.

This book constitutes the proceedings of the 14th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2018, held in Guildford, UK, in July 2018. The 52 full papers were carefully reviewed and selected from 62 initial submissions. As research topics the papers encompass a wide range of general mixtures of latent variables models but also theories and tools drawn from a great variety of disciplines such as structured tensor decompositions and applications; matrix and tensor factorizations; ICA methods; nonlinear mixtures; audio data and methods; signal separation evaluation campaign; deep learning and data-driven methods; advances in phase retrieval and applications; sparsity-related methods; and biomedical data and methods.

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