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» On the Performance of Clustering in Hilbert Spaces
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DAGM
2011
Springer
12 years 7 months ago
Relaxed Exponential Kernels for Unsupervised Learning
Many unsupervised learning algorithms make use of kernels that rely on the Euclidean distance between two samples. However, the Euclidean distance is optimal for Gaussian distribut...
Karim T. Abou-Moustafa, Mohak Shah, Fernando De la...
KDD
2006
ACM
156views Data Mining» more  KDD 2006»
14 years 8 months ago
Discovering significant OPSM subspace clusters in massive gene expression data
Order-preserving submatrixes (OPSMs) have been accepted as a biologically meaningful subspace cluster model, capturing the general tendency of gene expressions across a subset of ...
Byron J. Gao, Obi L. Griffith, Martin Ester, Steve...
MIR
2003
ACM
174views Multimedia» more  MIR 2003»
14 years 25 days ago
Content-based image retrieval by clustering
In a typical content-based image retrieval (CBIR) system, query results are a set of images sorted by feature similarities with respect to the query. However, images with high fea...
Yixin Chen, James Ze Wang, Robert Krovetz
CLUSTER
2009
IEEE
13 years 11 months ago
Using a cluster as a memory resource: A fast and large virtual memory on MPI
—The 64-bit OS provides ample memory address space that is beneficial for applications using a large amount of data. This paper proposes using a cluster as a memory resource for...
Hiroko Midorikawa, Kazuhiro Saito, Mitsuhisa Sato,...
BMCBI
2005
122views more  BMCBI 2005»
13 years 7 months ago
GenClust: A genetic algorithm for clustering gene expression data
Background: Clustering is a key step in the analysis of gene expression data, and in fact, many classical clustering algorithms are used, or more innovative ones have been designe...
Vito Di Gesù, Raffaele Giancarlo, Giosu&egr...