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» Boosting Methods for Regression
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ICASSP
2011
IEEE
14 years 6 months ago
Joint Bayesian removal of impulse and background noise
We present a method for the removal of noise including nonGaussian impulses from a signal. Impulse noise is removed jointly a homogenous Gaussian noise floor using a Gabor regres...
James Murphy, Simon J. Godsill
266
Voted
DAGM
2011
Springer
14 years 2 months ago
Real Time Head Pose Estimation from Consumer Depth Cameras
We present a system for estimating location and orientation of a person’s head, from depth data acquired by a low quality device. Our approach is based on discriminative random r...
Gabriele Fanelli, Thibaut Weise, Juergen Gall, Luc...
250
Voted
ICDE
2008
IEEE
203views Database» more  ICDE 2008»
16 years 3 months ago
Training Linear Discriminant Analysis in Linear Time
Linear Discriminant Analysis (LDA) has been a popular method for extracting features which preserve class separability. It has been widely used in many fields of information proces...
Deng Cai, Xiaofei He, Jiawei Han
121
Voted
ICML
2004
IEEE
16 years 3 months ago
The Bayesian backfitting relevance vector machine
Traditional non-parametric statistical learning techniques are often computationally attractive, but lack the same generalization and model selection abilities as state-of-the-art...
Aaron D'Souza, Sethu Vijayakumar, Stefan Schaal
KDD
2006
ACM
165views Data Mining» more  KDD 2006»
16 years 3 months ago
Training linear SVMs in linear time
Linear Support Vector Machines (SVMs) have become one of the most prominent machine learning techniques for highdimensional sparse data commonly encountered in applications like t...
Thorsten Joachims