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ICML
2009
IEEE
15 years 11 months ago
Fast evolutionary maximum margin clustering
The maximum margin clustering approach is a recently proposed extension of the concept of support vector machines to the clustering problem. Briefly stated, it aims at finding a...
Fabian Gieseke, Tapio Pahikkala, Oliver Kramer
IJCNN
2007
IEEE
15 years 10 months ago
Spectral Clustering of Synchronous Spike Trains
— In this paper a clustering algorithm that learns the groups of synchronized spike trains directly from data is proposed. Clustering of spike trains based on the presence of syn...
António R. C. Paiva, Sudhir Rao, Il Park, J...
ICCS
2005
Springer
15 years 10 months ago
Dimension Reduction for Clustering Time Series Using Global Characteristics
Existing methods for time series clustering rely on the actual data values can become impractical since the methods do not easily handle dataset with high dimensionality, missing v...
Xiaozhe Wang, Kate A. Smith, Rob J. Hyndman
KDD
1997
ACM
72views Data Mining» more  KDD 1997»
15 years 8 months ago
Detecting Atmospheric Regimes Using Cross-Validated Clustering
Low-frequency variability in geopotential height records of the Northern Hemisphere is a topic of significance in atmospheric science, having profound implications for climate mod...
Padhraic Smyth, Michael Ghil, Kayo Ide, Joseph Rod...
ICPR
2010
IEEE
15 years 7 months ago
Probabilistic Clustering Using the Baum-Eagon Inequality
The paper introduces a framework for clustering data objects in a similarity-based context. The aim is to cluster objects into a given number of classes without imposing a hard pa...
Samuel Rota Bulo', Marcello Pelillo