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» Random Projection for High Dimensional Data Clustering: A Cl...
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ICPR
2004
IEEE
14 years 9 months ago
A Hierarchical Projection Pursuit Clustering Algorithm
We define a cluster to be characterized by regions of high density separated by regions that are sparse. By observing the downward closure property of density, the search for inte...
Alexei D. Miasnikov, Jayson E. Rome, Robert M. Har...
SDM
2007
SIAM
98views Data Mining» more  SDM 2007»
13 years 10 months ago
An incremental data-stream sketch using sparse random projections
We propose the use of random projections with a sparse matrix to maintain a sketch of a collection of high-dimensional data-streams that are updated asynchronously. This sketch al...
Aditya Krishna Menon, Gia Vinh Anh Pham, Sanjay Ch...
KDD
2002
ACM
194views Data Mining» more  KDD 2002»
14 years 9 months ago
Scale Space Exploration For Mining Image Information Content
Images are highly complex multidimensional signals, with rich and complicated information content. For this reason they are difficult to analyze through a unique automated approach...
Mariana Ciucu, Patrick Héas, Mihai Datcu, J...
CSB
2003
IEEE
150views Bioinformatics» more  CSB 2003»
14 years 1 months ago
Algorithms for Bounded-Error Correlation of High Dimensional Data in Microarray Experiments
The problem of clustering continuous valued data has been well studied in literature. Its application to microarray analysis relies on such algorithms as -means, dimensionality re...
Mehmet Koyutürk, Ananth Grama, Wojciech Szpan...
ICDM
2008
IEEE
146views Data Mining» more  ICDM 2008»
14 years 3 months ago
Hunting for Coherent Co-clusters in High Dimensional and Noisy Datasets
Clustering problems often involve datasets where only a part of the data is relevant to the problem, e.g., in microarray data analysis only a subset of the genes show cohesive exp...
Meghana Deodhar, Joydeep Ghosh, Gunjan Gupta, Hyuk...