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» Training Invariant Support Vector Machines
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133
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IJISTA
2007
124views more  IJISTA 2007»
15 years 3 months ago
Incremental learning for spoken affect classification and its application in call-centres
: This paper introduces a system for real-time incremental learning in a call-centre environment. The classifier used is a Support Vector Machine (SVM) and it is applied to telepho...
Donn Morrison, Ruili Wang, W. L. Xu, Liyanage C. D...
127
Voted
ICPR
2004
IEEE
16 years 4 months ago
Sequence Recognition with Scanning N-Tuple Ensembles
The Scanning N-Tuple classifier (SNT) is a fast and accurate method for classifying sequences. Applications include both on-line and off-line hand-written character recognition. S...
Simon M. Lucas, Tzu-Kuo Huang
107
Voted
TSP
2008
135views more  TSP 2008»
15 years 3 months ago
Nonlinear Channel Equalization With Gaussian Processes for Regression
We propose Gaussian processes for regression as a novel nonlinear equalizer for digital communications receivers. GPR's main advantage, compared to previous nonlinear estimat...
Fernando Pérez-Cruz, Juan José Muril...
IJCNN
2007
IEEE
15 years 10 months ago
Agnostic Learning versus Prior Knowledge in the Design of Kernel Machines
Abstract— The optimal model parameters of a kernel machine are typically given by the solution of a convex optimisation problem with a single global optimum. Obtaining the best p...
Gavin C. Cawley, Nicola L. C. Talbot
154
Voted
ECCV
2008
Springer
16 years 5 months ago
Relevant Feature Selection for Human Pose Estimation and Localization in Cluttered Images
Abstract. We address the problem of estimating human body pose from a single image with cluttered background. We train multiple local linear regressors for estimating the 3D pose f...
Ryuzo Okada, Stefano Soatto