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ECML
2001
Springer
15 years 7 months ago
Iterative Double Clustering for Unsupervised and Semi-supervised Learning
We present a powerful meta-clustering technique called Iterative Double Clustering (IDC). The IDC method is a natural extension of the recent Double Clustering (DC) method of Slon...
Ran El-Yaniv, Oren Souroujon
NIPS
2008
15 years 4 months ago
Adaptive Template Matching with Shift-Invariant Semi-NMF
How does one extract unknown but stereotypical events that are linearly superimposed within a signal with variable latencies and variable amplitudes? One could think of using temp...
Jonathan Le Roux, Alain de Cheveigné, Lucas...
CORR
2010
Springer
249views Education» more  CORR 2010»
15 years 2 months ago
Performance Analysis of Spectral Clustering on Compressed, Incomplete and Inaccurate Measurements
Spectral clustering is one of the most widely used techniques for extracting the underlying global structure of a data set. Compressed sensing and matrix completion have emerged a...
Blake Hunter, Thomas Strohmer
138
Voted
JMLR
2008
131views more  JMLR 2008»
15 years 2 months ago
On Relevant Dimensions in Kernel Feature Spaces
We show that the relevant information of a supervised learning problem is contained up to negligible error in a finite number of leading kernel PCA components if the kernel matche...
Mikio L. Braun, Joachim M. Buhmann, Klaus-Robert M...
119
Voted
TC
2008
15 years 2 months ago
STAR : An Efficient Coding Scheme for Correcting Triple Storage Node Failures
Proper data placement schemes based on erasure correcting code are one of the most important components for a highly available data storage system. For such schemes, low decoding ...
Cheng Huang, Lihao Xu