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» Semi-supervised time series classification
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KDD
2009
ACM
192views Data Mining» more  KDD 2009»
14 years 8 months ago
Time series shapelets: a new primitive for data mining
Classification of time series has been attracting great interest over the past decade. Recent empirical evidence has strongly suggested that the simple nearest neighbor algorithm ...
Lexiang Ye, Eamonn J. Keogh
ISBI
2006
IEEE
14 years 8 months ago
Application of temporal texture features to automated analysis of protein subcellular locations in time series fluorescence micr
Protein subcellular locations, as an important property of proteins, are commonly learned using fluorescence microscopy. Previous work by our group has shown that automated analys...
Yanhua Hu, Jesus Carmona, Robert F. Murphy
ICDM
2009
IEEE
121views Data Mining» more  ICDM 2009»
14 years 2 months ago
Finding Time Series Motifs in Disk-Resident Data
—Time series motifs are sets of very similar subsequences of a long time series. They are of interest in their own right, and are also used as inputs in several higher-level data...
Abdullah Mueen, Eamonn J. Keogh, Nima Bigdely Sham...
DAGSTUHL
2006
13 years 9 months ago
Application of Kolmogorov complexity and universal codes to identity testing and nonparametric testing of serial independence fo
We show that Kolmogorov complexity and such its estimators as universal codes (or data compression methods) can be applied for hypothesis testing in a framework of classical mathe...
Boris Ryabko, Jaakko Astola, Alexander Gammerman
CORR
2006
Springer
91views Education» more  CORR 2006»
13 years 7 months ago
Universal Codes as a Basis for Time Series Testing
We suggest a new approach to hypothesis testing for ergodic and stationary processes. In contrast to standard methods, the suggested approach gives a possibility to make tests, ba...
Boris Ryabko, Jaakko Astola