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» Predicting Time Series with Support Vector Machines
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ICPR
2002
IEEE
15 years 11 months ago
Object Detection in Images: Run-Time Complexity and Parameter Selection of Support Vector Machines
In this paper we address two aspects related to the exploitation of Support Vector Machines (SVM) for classification in real application domains, such as the detection of objects ...
Nicola Ancona, Grazia Cicirelli, Ettore Stella, Ar...
ICASSP
2009
IEEE
15 years 4 months ago
Combining VTS model compensation and support vector machines
It is difficult to adapt discriminative classifiers, particularly kernel based ones such as support vector machines (SVMs), to handle mismatches between the training and test da...
Mark J. F. Gales, Federico Flego
JMLR
2006
91views more  JMLR 2006»
14 years 9 months ago
QP Algorithms with Guaranteed Accuracy and Run Time for Support Vector Machines
We describe polynomial
Don R. Hush, Patrick Kelly, Clint Scovel, Ingo Ste...
ICDM
2007
IEEE
109views Data Mining» more  ICDM 2007»
15 years 4 months ago
A Support Vector Approach to Censored Targets
Censored targets, such as the time to events in survival analysis, can generally be represented by intervals on the real line. In this paper, we propose a novel support vector tec...
Pannagadatta K. Shivaswamy, Wei Chu, Martin Jansch...
MLDM
2009
Springer
15 years 4 months ago
Memory-Based Modeling of Seasonality for Prediction of Climatic Time Series
The paper describes a method for predicting climate time series that consist of significant annual and diurnal seasonal components and a short-term stockastic component. A memory...
Daniel Nikovski, Ganesan Ramachandran