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128
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ECML
2007
Springer
15 years 7 months ago
Principal Component Analysis for Large Scale Problems with Lots of Missing Values
Abstract. Principal component analysis (PCA) is a well-known classical data analysis technique. There are a number of algorithms for solving the problem, some scaling better than o...
Tapani Raiko, Alexander Ilin, Juha Karhunen
93
Voted
GECCO
2007
Springer
162views Optimization» more  GECCO 2007»
15 years 7 months ago
A multi-objective approach to discover biclusters in microarray data
The main motivation for using a multi–objective evolutionary algorithm for finding biclusters in gene expression data is motivated by the fact that when looking for biclusters ...
Federico Divina, Jesús S. Aguilar-Ruiz
ICCS
2007
Springer
15 years 7 months ago
Hessian-Based Model Reduction for Large-Scale Data Assimilation Problems
Assimilation of spatially- and temporally-distributed state observations into simulations of dynamical systems stemming from discretized PDEs leads to inverse problems with high-di...
Omar Bashir, Omar Ghattas, Judith Hill, Bart G. va...
87
Voted
ICMI
2007
Springer
160views Biometrics» more  ICMI 2007»
15 years 7 months ago
Using the influence model to recognize functional roles in meetings
In this paper, an influence model is used to recognize functional roles played during meetings. Previous works on the same corpus demonstrated a high recognition accuracy using SV...
Wen Dong, Bruno Lepri, Alessandro Cappelletti, Ale...
105
Voted
MIRAGE
2007
Springer
15 years 6 months ago
Model-Based Feature Extraction for Gait Analysis and Recognition
Human motion analysis has received a great attention from researchers in the last decade due to its potential use in different applications. We propose a new approach to extract h...
Imed Bouchrika, Mark S. Nixon