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» Supervised dimensionality reduction using mixture models
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ICCAD
2006
IEEE
152views Hardware» more  ICCAD 2006»
15 years 8 months ago
Performance-oriented statistical parameter reduction of parameterized systems via reduced rank regression
Process variations in modern VLSI technologies are growing in both magnitude and dimensionality. To assess performance variability, complex simulation and performance models param...
Zhuo Feng, Peng Li
ICASSP
2011
IEEE
14 years 3 months ago
Subspace pursuit method for kernel-log-linear models
This paper presents a novel method for reducing the dimensionality of kernel spaces. Recently, to maintain the convexity of training, loglinear models without mixtures have been u...
Yotaro Kubo, Simon Wiesler, Ralf Schlüter, He...
VISUAL
2005
Springer
15 years 5 months ago
Face Recognition Using Modular Bilinear Discriminant Analysis
We present a Modular Bilinear Disciminant Analysis (MBDA) approach for face recognition. A set of classifiers are trained independently on specific face regions, and different c...
Muriel Visani, Christophe Garcia, Jean-Michel Joli...
CVPR
2011
IEEE
14 years 7 months ago
Supervised Local Subspace Learning for Continuous Head Pose Estimation
Head pose estimation from images has recently attracted much attention in computer vision due to its diverse applications in face recognition, driver monitoring and human computer...
Dong Huang, Markus Storer, Fernando DelaTorre, Hor...
GECCO
2006
Springer
265views Optimization» more  GECCO 2006»
15 years 3 months ago
Cutting stock waste reduction using genetic algorithms
A new model for the One-dimensional Cutting Stock problem using Genetic Algorithms (GA) is developed to optimize construction steel bars waste. One-dimensional construction stocks...
Yaser M. A. Khalifa, O. Salem, A. Shahin