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KDD
2006
ACM
145views Data Mining» more  KDD 2006»
16 years 7 months ago
Deriving quantitative models for correlation clusters
Correlation clustering aims at grouping the data set into correlation clusters such that the objects in the same cluster exhibit a certain density and are all associated to a comm...
Arthur Zimek, Christian Böhm, Elke Achtert, H...
BMCBI
2010
153views more  BMCBI 2010»
15 years 6 months ago
Challenges in microarray class discovery: a comprehensive examination of normalization, gene selection and clustering
Background: Cluster analysis, and in particular hierarchical clustering, is widely used to extract information from gene expression data. The aim is to discover new classes, or su...
Eva Freyhult, Mattias Landfors, Jenny Önskog,...
ICDAR
2007
IEEE
16 years 29 days ago
Streaming-Archival InkML Conversion
Ink Markup Language (InkML) provides a platform– neutral data format that can be used to represent, store and transmit digital ink data. Both streaming and archival applications...
Birendra Keshari, Stephen M. Watt
CORR
2008
Springer
118views Education» more  CORR 2008»
15 years 6 months ago
Sum Rate Maximization using Linear Precoding and Decoding in the Multiuser MIMO Downlink
Abstract--We propose an algorithm to maximize the instantaneous sum data rate transmitted by a base station in the downlink of a multiuser multiple-input, multiple-output system. T...
Adam J. Tenenbaum, Raviraj S. Adve
ICDM
2003
IEEE
71views Data Mining» more  ICDM 2003»
15 years 12 months ago
Tree-structured Partitioning Based on Splitting Histograms of Distances
We propose a novel clustering algorithm that is similar in spirit to classification trees. The data is recursively split using a criterion that applies a discrete curve evolution...
Longin Jan Latecki, Rajagopal Venugopal, Marc Sobe...