Latent Variable Analysis and Signal Separation
14th International Conference, LVA/ICA 2018, Guildford, UK, July 2–5, 2018, Proceedings
Nonfiction, Computers, Advanced Computing, Engineering, Computer Vision, Application Software, Computer Graphics, General Computing
| Author: | ISBN: | 9783319937649 | |
| Publisher: | Springer International Publishing | Publication: | June 5, 2018 |
| Imprint: | Springer | Language: | English |
| Author: | |
| ISBN: | 9783319937649 |
| Publisher: | Springer International Publishing |
| Publication: | June 5, 2018 |
| Imprint: | Springer |
| Language: | English |
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.
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.
