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Latent Variable Analysis and Signal Separation

14th International Conference, LVA/ICA 2018, Guildford, UK, July 2–5, 2018, Proceedings

  • Conference proceedings
  • © 2018

Overview

Editors:
  1. Yannick Deville

    1. Paul Sabatier University, Toulouse, France

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  2. Sharon Gannot

    1. Bar-Ilan University, Ramat Gan, Israel

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  3. Russell Mason

    1. University of Surrey, Guildford, United Kingdom

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  4. Mark D. Plumbley

    1. University of Surrey, Guildford, United Kingdom

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  5. Dominic Ward

    1. University of Surrey, Guildford, United Kingdom

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 10891)

Part of the book sub series: Theoretical Computer Science and General Issues (LNTCS)

Included in the following conference series:

Conference proceedings info: LVA/ICA 2018.

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Table of contents (52 papers)

  1. Front Matter

    Pages I-XVII
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  2. Structured Tensor Decompositions and Applications

    1. Front Matter

      Pages 1-1
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    2. Robust Multilinear Decomposition of Low Rank Tensors

      • Xu Han, Laurent Albera, Amar Kachenoura, Huazhong Shu, Lotfi Senhadji
      Pages 3-12

    3. Multichannel Audio Modeling with Elliptically Stable Tensor Decomposition

      • Mathieu Fontaine, Fabian-Robert Stöter, Antoine Liutkus, Umut Şimşekli, Romain Serizel, Roland Badeau
      Pages 13-23

    4. Sum Conditioned Poisson Factorization

      • Gökhan Çapan, Semih Akbayrak, Taha Yusuf Ceritli, Ali Taylan Cemgil
      Pages 24-35

    5. Curve Registered Coupled Low Rank Factorization

      • Jeremy Emile Cohen, Rodrigo Cabral Farias, Bertrand Rivet
      Pages 36-45

    6. Source Analysis and Selection Using Block Term Decomposition in Atrial Fibrillation

      • Pedro Marinho R. de Oliveira, Vicente Zarzoso
      Pages 46-56

    7. Some Issues in Computing the CP Decomposition of NonNegative Tensors

      • Mohamad Jouni, Mauro Dalla Mura, Pierre Comon
      Pages 57-66

  3. Matrix and Tensor Factorizations

    1. Front Matter

      Pages 67-67
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    2. A Grassmannian Minimum Enclosing Ball Approach for Common Subspace Extraction

      • Emilie Renard, Kyle A. Gallivan, P.-A. Absil
      Pages 69-78

    3. Decoupling Multivariate Functions Using Second-Order Information and Tensors

      • Philippe Dreesen, Jeroen De Geeter, Mariya Ishteva
      Pages 79-88

    4. Nonnegative PARAFAC2: A Flexible Coupling Approach

      • Jeremy E. Cohen, Rasmus Bro
      Pages 89-98

    5. Applications of Polynomial Common Factor Computation in Signal Processing

      • Ivan Markovsky, Antonio Fazzi, Nicola Guglielmi
      Pages 99-106

    6. Joint Nonnegative Matrix Factorization for Underdetermined Blind Source Separation in Nonlinear Mixtures

      • Ivica Kopriva
      Pages 107-115

    7. Image Completion with Nonnegative Matrix Factorization Under Separability Assumption

      • Tomasz Sadowski, Rafał Zdunek
      Pages 116-126

    8. Feature Selection in Weakly Coherent Matrices

      • Stéphane Chrétien, Olivier Ho
      Pages 127-138

    9. Variable Projection Applied to Block Term Decomposition of Higher-Order Tensors

      • Guillaume Olikier, P.-A. Absil, Lieven De Lathauwer
      Pages 139-148

  4. ICA Methods

    1. Front Matter

      Pages 149-149
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    2. Accelerating Likelihood Optimization for ICA on Real Signals

      • Pierre Ablin, Jean-François Cardoso, Alexandre Gramfort
      Pages 151-160

    3. Orthogonally-Constrained Extraction of Independent Non-Gaussian Component from Non-Gaussian Background Without ICA

      • Zbyněk Koldovský, Petr Tichavský, Nobutaka Ono
      Pages 161-170
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Other volumes

  1. Latent Variable Analysis and Signal Separation

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About this book

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.

Editors and Affiliations

  • Paul Sabatier University, Toulouse, France

    Yannick Deville

  • Bar-Ilan University, Ramat Gan, Israel

    Sharon Gannot

  • University of Surrey, Guildford, United Kingdom

    Russell Mason, Mark D. Plumbley, Dominic Ward

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