Advances in independent component analysis and learning machines. (2015)

• Record Type: Book
• Further Information: Note: Edited by Ella Bingham, Samuel Kaski, Jorma Laaksonen, Jouko Lampinen.
• Editors: Bingham, Ella; Kaski, Samuel; Laaksonen, Jorma; Lampinen, Jouko
• Contents: Prologue: Sketching a Scholar Part 1: Methods Chapter 1. The Initial Convergence Rate of the FastICA Algorithm: The "One-Third Rule" Chapter 2. Improved variants of the FastICA algorithm Chapter 3. A unified probabilistic model for independent and principal component analysis Chapter 4. Riemannian optimization in complex-valued ICA Chapter 5. Non-Additive Optimization Chapter 6. Image denoising via local factor analysis under Bayesian Ying-Yang principle Chapter 7. Unsupervised Deep Learning: A Short Review Chapter 8. From Neural PCA to Deep Unsupervised Learning Part 2: Applications Chapter 9. Two Decades of Local Binary Patterns – A Survey Chapter 10. Subspace approach in Spectral Color Science Chapter 11. From pattern recognition methods to machine vision applications Chapter 12. Advances in Visual Concept Detection: Ten Years of TRECVID Chapter 13. On the applicability of latent variable modeling to research system data
• Publisher Details: Amsterdam : Academic Press
• Publication Date: 2015
• Extent: 1 online resource
• Subjects: 004; Independent component analysis
• Languages: English
• ISBNs: 9780128028070
• Related ISBNs: 9780128028063
• Notes: Note: Description based on CIP data; item not viewed.
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.