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» Clustering with the Connectivity Kernel
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NIPS
2008
13 years 10 months ago
Dimensionality Reduction for Data in Multiple Feature Representations
In solving complex visual learning tasks, adopting multiple descriptors to more precisely characterize the data has been a feasible way for improving performance. These representa...
Yen-Yu Lin, Tyng-Luh Liu, Chiou-Shann Fuh
FTML
2010
159views more  FTML 2010»
13 years 7 months ago
Dimension Reduction: A Guided Tour
We give a tutorial overview of several geometric methods for dimension reduction. We divide the methods into projective methods and methods that model the manifold on which the da...
Christopher J. C. Burges
ICASSP
2011
IEEE
13 years 21 days ago
Adaptive N-normalization for enhancing music similarity
The N-Normalization is an efficient method for normalizing a given similarity computed among multimedia objects. It can be considered for clustering and kernel enhancement. Howev...
Mathieu Lagrange, George Tzanetakis
CCGRID
2003
IEEE
14 years 2 months ago
Improved Read Performance in a Cost-Effective, Fault-Tolerant Parallel Virtual File System (CEFT-PVFS)
Due to the ever-widening performance gap between processors and disks, I/O operations tend to become the major performance bottleneck of data-intensive applications on modern clus...
Yifeng Zhu, Hong Jiang, Xiao Qin, Dan Feng, David ...
CVPR
2007
IEEE
14 years 11 months ago
On the Blind Classification of Time Series
We propose a cord distance in the space of dynamical models that takes into account their dynamics, including transients, output maps and input distributions. In data analysis app...
Alessandro Bissacco, Stefano Soatto