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» A new evolutionary method for time series forecasting
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ICDE
2005
IEEE
185views Database» more  ICDE 2005»
14 years 9 months ago
A Multiresolution Symbolic Representation of Time Series
Efficiently and accurately searching for similarities among time series and discovering interesting patterns is an important and non-trivial problem. In this paper, we introduce a...
Vasileios Megalooikonomou, Qiang Wang, Guo Li, Chr...
NIPS
2003
13 years 9 months ago
Dynamical Modeling with Kernels for Nonlinear Time Series Prediction
We consider the question of predicting nonlinear time series. Kernel Dynamical Modeling (KDM), a new method based on kernels, is proposed as an extension to linear dynamical model...
Liva Ralaivola, Florence d'Alché-Buc
ICSE
2010
IEEE-ACM
14 years 14 days ago
An eclectic approach for change impact analysis
Change impact analysis aims at identifying software artifacts being affected by a change. In the past, this problem has been addressed by approaches relying on static, dynamic, a...
Michele Ceccarelli, Luigi Cerulo, Gerardo Canfora,...
ML
2000
ACM
157views Machine Learning» more  ML 2000»
13 years 7 months ago
A Multistrategy Approach to Classifier Learning from Time Series
We present an approach to inductive concept learning using multiple models for time series. Our objective is to improve the efficiency and accuracy of concept learning by decomposi...
William H. Hsu, Sylvian R. Ray, David C. Wilkins
JMLR
2011
187views more  JMLR 2011»
13 years 2 months ago
Robust Statistics for Describing Causality in Multivariate Time Series
A widely agreed upon definition of time series causality inference, established in the seminal 1969 article of Clive Granger (1969), is based on the relative ability of the histor...
Florin Popescu