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IJCNN
2007
IEEE
16 years 12 days 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
TOG
2012
245views Communications» more  TOG 2012»
13 years 8 months ago
How do humans sketch objects?
Humans have used sketching to depict our visual world since prehistoric times. Even today, sketching is possibly the only rendering technique readily available to all humans. This...
Mathias Eitz, James Hays, Marc Alexa
ECCV
2008
Springer
16 years 8 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
KDD
2000
ACM
153views Data Mining» more  KDD 2000»
15 years 9 months ago
The generalized Bayesian committee machine
In this paper we introduce the Generalized Bayesian Committee Machine (GBCM) for applications with large data sets. In particular, the GBCM can be used in the context of kernel ba...
Volker Tresp
PKDD
2009
Springer
138views Data Mining» more  PKDD 2009»
16 years 20 days ago
Margin and Radius Based Multiple Kernel Learning
A serious drawback of kernel methods, and Support Vector Machines (SVM) in particular, is the difficulty in choosing a suitable kernel function for a given dataset. One of the appr...
Huyen Do, Alexandros Kalousis, Adam Woznica, Melan...