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CVPR
2010
IEEE
13 years 5 months ago
Robust RVM regression using sparse outlier model
Kernel regression techniques such as Relevance Vector Machine (RVM) regression, Support Vector Regression and Gaussian processes are widely used for solving many computer vision p...
Kaushik Mitra, Ashok Veeraraghavan, Rama Chellappa
IROS
2007
IEEE
171views Robotics» more  IROS 2007»
13 years 11 months ago
A Kalman filter for robust outlier detection
— In this paper, we introduce a modified Kalman filter that can perform robust, real-time outlier detection in the observations, without the need for parameter tuning. Robotic ...
Jo-Anne Ting, Evangelos Theodorou, Stefan Schaal
ECML
2007
Springer
13 years 11 months ago
Learning an Outlier-Robust Kalman Filter
We introduce a modified Kalman filter that performs robust, real-time outlier detection, without the need for manual parameter tuning by the user. Systems that rely on high quali...
Jo-Anne Ting, Evangelos Theodorou, Stefan Schaal
ICMCS
2006
IEEE
142views Multimedia» more  ICMCS 2006»
13 years 11 months ago
Music Signal Synthesis using Sinusoid Models and Sliding-Window Esprit
This paper proposes a music signal synthesis scheme that is based on sinusoid modeling and sliding-window ESPRIT. Despite widely used audio coding standards, effectively synthesiz...
Anders Gunnarsson, Irene Gu
CSDA
2008
158views more  CSDA 2008»
13 years 5 months ago
Outlier identification in high dimensions
A computationally fast procedure for identifying outliers is presented, that is particularly effective in high dimensions. This algorithm utilizes simple properties of principal c...
Peter Filzmoser, Ricardo A. Maronna, Mark Werner