Advances in Independent Component Analysis and Learning Machines (Elsevier), edited by Ella Bingham, Samuel Kaski, Jorma Laaksonen and Jouko Lampinen, is collected in honour of Professor Erkki Oja, one of the pioneers of Independent Component Analysis (ICA). The book reviews recent advances in the theory and application of ICA, as well as its influence on signal processing, pattern recognition, machine learning, and data mining.
Examples of topics which have developed from the advances of ICA and machine learning, which are covered in the book are:
- A unifying probabilistic model for PCA and ICA
- Optimization methods for matrix decompositions
- Insights into the FastICA algorithm
- Unsupervised deep learning
- Machine vision, and image and video retrieval
See more details on Aalto Distinguished Professor Erkki Oja at http://www.aalto.fi/en/current/news/2015-01-30-002/
The book is available via Elsevier: http://store.elsevier.com/Advances-in-Independent-Component-Analysis-and-Learning-Machines/isbn-9780128028063/
More information from: Ella Bingham firstname.lastname@aalto.fi
Last updated on 29 Apr 2015 by Noora Suominen de Rios - Page created on 29 Apr 2015 by Noora Suominen de Rios