© 2015

Latent Variable Analysis and Signal Separation

12th International Conference, LVA/ICA 2015, Liberec, Czech Republic, August 25-28, 2015, Proceedings

  • Emmanuel Vincent
  • Arie Yeredor
  • Zbyněk Koldovský
  • Petr Tichavský
Conference proceedings LVA/ICA 2015

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9237)

Also part of the Theoretical Computer Science and General Issues book sub series (LNTCS, volume 9237)

Table of contents

  1. Front Matter
    Pages I-XVI
  2. Tensor-Based Methods for Blind Signal Separation

    1. Front Matter
      Pages 1-1
    2. Philippe Dreesen, Thomas Goossens, Mariya Ishteva, Lieven De Lathauwer, Johan Schoukens
      Pages 14-21
    3. Anh-Huy Phan, Petr Tichavský, Andrzej Cichocki
      Pages 31-40
    4. Mariya Ishteva
      Pages 49-55
    5. Jianshu Zhang, Ahmad Nimr, Kristina Naskovska, Martin Haardt
      Pages 64-72
  3. Deep Neural Networks for Supervised Speech Separation/Enhancement

    1. Front Matter
      Pages 73-73
    2. Tian Gao, Jun Du, Yong Xu, Cong Liu, Li-Rong Dai, Chin-Hui Lee
      Pages 75-82
    3. Jitong Chen, Yuxuan Wang, DeLiang Wang
      Pages 83-90
    4. Felix Weninger, Hakan Erdogan, Shinji Watanabe, Emmanuel Vincent, Jonathan Le Roux, John R. Hershey et al.
      Pages 91-99
  4. Joint Analysis of Multiple Datasets, Data Fusion, and Related Topics

    1. Front Matter
      Pages 109-109
    2. Dana Lahat, Christian Jutten
      Pages 111-118
    3. Rodrigo Cabral Farias, Jérémy Emile Cohen, Christian Jutten, Pierre Comon
      Pages 119-126
    4. Ofir Lindenbaum, Arie Yeredor, Moshe Salhov
      Pages 127-134
    5. Antoine Liutkus, Umut Şimşekli, A. Taylan Cemgil
      Pages 135-142

About these proceedings


This book constitutes the proceedings of the 12th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICS 2015, held in Liberec, Czech Republic, in August 2015. The 61 revised full papers presented – 29 accepted as oral presentations and 32 accepted as poster presentations – were carefully reviewed and selected from numerous submissions. Five special topics are addressed: tensor-based methods for blind signal separation; deep neural networks for supervised speech separation/enhancement; joined analysis of multiple datasets, data fusion, and related topics; advances in nonlinear blind source separation; sparse and low rank modeling for acoustic signal processing.


audio signal processing augmented statistics classification computational imaging decision trees deep learning empirical kernel maps environmental monitoring independent vector analysis joint block diagonalization medical imaging mobile sensor network multilinear algebra real-time similarity measures sparse modeling speech separation statistical modeling supervised learning texture analysis

Editors and affiliations

  • Emmanuel Vincent
    • 1
  • Arie Yeredor
    • 2
  • Zbyněk Koldovský
    • 3
  • Petr Tichavský
    • 4
  1. 1.InriaVillers-les-NancyFrance
  2. 2.Tel Aviv UniversityTel-AvivIsrael
  3. 3.Technical University of LibereLiberecCzech Republic
  4. 4.The Czech Academy of SciencesPragueCzech Republic

Bibliographic information