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{ "item_title" : "Latent Variable Analysis and Signal Separation", "item_author" : [" Yannick Deville", "Sharon Gannot", "Russell Mason "], "item_description" : "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.", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/3/31/993/763/3319937634_b.jpg", "price_data" : { "retail_price" : "54.99", "online_price" : "54.99", "our_price" : "54.99", "club_price" : "54.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Latent Variable Analysis and Signal Separation|Yannick Deville

Latent Variable Analysis and Signal Separation : 14th International Conference, Lva/Ica 2018, Guildford, Uk, July 2-5, 2018, Proceedings

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Overview

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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Details

  • ISBN-13: 9783319937632
  • ISBN-10: 3319937634
  • Publisher: Springer
  • Publish Date: June 2018
  • Dimensions: 9.21 x 6.14 x 1.21 inches
  • Shipping Weight: 1.83 pounds
  • Page Count: 580

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