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Carmona, Pedro Latorre

Mathematical Methodologies in Pattern Recognition and Machine Learning

Carmona, Pedro Latorre - Mathematical Methodologies in Pattern Recognition and Machine Learning, ebook

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ISBN: 9781461450764
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Table of contents

1. On the Expressivity of Alignment-Based Distance and Similarity Measures on Sequences and Trees in Inducing Orderings
Martin Emms, Hector-Hugo Franco-Penya

2. Automatic Annotation of a Dynamic Corpus by Label Propagation
Thomas Lansdall-Welfare, Ilias Flaounas, Nello Cristianini

3. Computing Voronoi Adjacencies in High Dimensional Spaces by Using Linear Programming
Juan Mendez, Javier Lorenzo

4. Phase-Locked Matrix Factorization with Estimation of the Common Oscillation
Miguel Almeida, Ricardo Vigário, José Bioucas-Dias

5. Stochastic Subgradient Estimation Training for Support Vector Machines
Sangkyun Lee, Stephen J. Wright

6. Single-Frame Signal Recovery Using a Similarity-Prior
Sakinah A. Pitchay, Ata Kabán

7. A Discretized Newton Flow for Time-Varying Linear Inverse Problems
Martin Kleinsteuber, Simon Hawe

8. Exploiting Structural Consistencies with Stacked Conditional Random Fields
Peter Kluegl, Martin Toepfer, Florian Lemmerich, Andreas Hotho, Frank Puppe

9. Detecting Mean-Reverted Patterns in Algorithmic Pairs Trading
K. Triantafyllopoulos, S. Han

10. Segmenting Carotid in CT Using Geometric Potential Field Deformable Model
Si Yong Yeo, Xianghua Xie, Igor Sazonov, Perumal Nithiarasu

11. A Robust Deformable Model for 3D Segmentation of the Left Ventricle from Ultrasound Data
Carlos Santiago, Jorge S. Marques, Jacinto C. Nascimento

12. Facial Expression Recognition Using Diffeomorphic Image Registration Framework
Bartlomiej W. Papiez, Bogdan J. Matuszewski, Lik-Kwan Shark, Wei Quan

Keywords: Mathematics, Systems Theory, Control, Optimization, Math Applications in Computer Science, Pattern Recognition

Author(s)
 
 
Publisher
Springer
Publication year
2013
Language
en
Edition
2013
Series
Springer Proceedings in Mathematics & Statistics
Page amount
8 pages
Category
Natural Sciences
Format
Ebook
eISBN (PDF)
9781461450764

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