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» Accelerated EM-based clustering of large data sets
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ICML
2009
IEEE
14 years 2 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
14 years 2 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...
BMCBI
2008
114views more  BMCBI 2008»
13 years 8 months ago
Visualizing and clustering high throughput sub-cellular localization imaging
Background: The expansion of automatic imaging technologies has created a need to be able to efficiently compare and review large sets of image data. To enable comparisons of imag...
Nicholas A. Hamilton, Rohan D. Teasdale
CVPR
2008
IEEE
14 years 10 months ago
Incremental learning of nonparametric Bayesian mixture models
Clustering is a fundamental task in many vision applications. To date, most clustering algorithms work in a batch setting and training examples must be gathered in a large group b...
Ryan Gomes, Max Welling, Pietro Perona
KAIS
2000
87views more  KAIS 2000»
13 years 7 months ago
An Index Structure for Data Mining and Clustering
Abstract. In this paper we present an index structure, called MetricMap, that takes a set of objects and a distance metric and then maps those objects to a k-dimensional space in s...
Xiong Wang, Jason Tsong-Li Wang, King-Ip Lin, Denn...