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» Dimensionality Reduction of Clustered Data Sets
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TSMC
2010
13 years 3 months ago
Distance Approximating Dimension Reduction of Riemannian Manifolds
We study the problem of projecting high-dimensional tensor data on an unspecified Riemannian manifold onto some lower dimensional subspace1 without much distorting the pairwise geo...
Changyou Chen, Junping Zhang, Rudolf Fleischer
IJON
2006
60views more  IJON 2006»
13 years 8 months ago
Spatiotemporal clustering of synchronized bursting events in neuronal networks
in vitro neuronal networks display Synchronized Bursting Events (SBEs), with characteristic temporal width of 100-500 ms and frequency of once every few seconds. We analyze such d...
Uri Barkan, David Horn
ICDE
2007
IEEE
165views Database» more  ICDE 2007»
14 years 10 months ago
On Randomization, Public Information and the Curse of Dimensionality
A key method for privacy preserving data mining is that of randomization. Unlike k-anonymity, this technique does not include public information in the underlying assumptions. In ...
Charu C. Aggarwal
KDD
2004
ACM
624views Data Mining» more  KDD 2004»
14 years 2 months ago
Programming the K-means clustering algorithm in SQL
Using SQL has not been considered an efficient and feasible way to implement data mining algorithms. Although this is true for many data mining, machine learning and statistical a...
Carlos Ordonez
WSC
2004
13 years 10 months ago
An Examination of Forward Volatility
This paper investigates the adequacy of various principal components (p.c.) approaches as data reduction schemes for processing contingent claim valuations on baskets of equities....
Ray Popovic, David Goldsman