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» Kernels for Semi-Structured Data
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ESANN
2003
13 years 11 months ago
Approximately unbiased estimation of conditional variance in heteroscedastic kernel ridge regression
In this paper we extend a form of kernel ridge regression for data characterised by a heteroscedastic noise process (introduced in Foxall et al. [1]) in order to provide approxima...
Gavin C. Cawley, Nicola L. C. Talbot, Robert J. Fo...
ICIP
2010
IEEE
13 years 8 months ago
Combining free energy score spaces with information theoretic kernels: Application to scene classification
Most approaches to learn classifiers for structured objects (e.g., images) use generative models in a classical Bayesian framework. However, state-of-the-art classifiers for vecto...
Manuele Bicego, Alessandro Perina, Vittorio Murino...
SDM
2009
SIAM
172views Data Mining» more  SDM 2009»
14 years 7 months ago
Travel-Time Prediction Using Gaussian Process Regression: A Trajectory-Based Approach.
This paper is concerned with the task of travel-time prediction for an arbitrary origin-destination pair on a map. Unlike most of the existing studies, which focus only on a parti...
Sei Kato, Tsuyoshi Idé
FDL
2006
IEEE
14 years 4 months ago
Design Structure Analysis and Transaction Recording in SystemC
We present an introspection/reflection framework for SystemC which extracts design-relevant structure information and transaction data under any LRM-2.1 compliant simulation kern...
Wolfgang Klingauf, Manuel Geffken
NIPS
2004
13 years 11 months ago
An Application of Boosting to Graph Classification
This paper presents an application of Boosting for classifying labeled graphs, general structures for modeling a number of real-world data, such as chemical compounds, natural lan...
Taku Kudo, Eisaku Maeda, Yuji Matsumoto