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» Lossy Reduction for Very High Dimensional Data
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69
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KDD
2004
ACM
118views Data Mining» more  KDD 2004»
15 years 10 months ago
Parallel computation of high dimensional robust correlation and covariance matrices
The computation of covariance and correlation matrices are critical to many data mining applications and processes. Unfortunately the classical covariance and correlation matrices...
James Chilson, Raymond T. Ng, Alan Wagner, Ruben H...
TKDE
2002
124views more  TKDE 2002»
14 years 9 months ago
Clustering for Approximate Similarity Search in High-Dimensional Spaces
In this paper we present a clustering and indexing paradigm called Clindex for high-dimensional search spaces. The scheme is designed for approximate similarity searches, where on...
Chen Li, Edward Y. Chang, Hector Garcia-Molina, Gi...
EDBT
2000
ACM
15 years 1 months ago
Dynamically Optimizing High-Dimensional Index Structures
In high-dimensional query processing, the optimization of the logical page-size of index structures is an important research issue. Even very simple query processing techniques suc...
Christian Böhm, Hans-Peter Kriegel
107
Voted
JMLR
2010
115views more  JMLR 2010»
14 years 4 months ago
O-IPCAC and its Application to EEG Classification
In this paper we describe an online/incremental linear binary classifier based on an interesting approach to estimate the Fisher subspace. The proposed method allows to deal with ...
Alessandro Rozza, Gabriele Lombardi, Marco Rosa, E...
SODA
2010
ACM
171views Algorithms» more  SODA 2010»
15 years 7 months ago
Coresets and Sketches for High Dimensional Subspace Approximation Problems
We consider the problem of approximating a set P of n points in Rd by a j-dimensional subspace under the p measure, in which we wish to minimize the sum of p distances from each p...
Dan Feldman, Morteza Monemizadeh, Christian Sohler...