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VISUALIZATION
2003
IEEE
14 years 2 months ago
Accelerating Large Data Analysis by Exploiting Regularities
We present techniques for discovering and exploiting regularity in large curvilinear data sets. The data can be based on a single mesh or a mesh composed of multiple submeshes (al...
David Ellsworth, Patrick J. Moran
IJAR
2010
106views more  IJAR 2010»
13 years 7 months ago
A minimum distance estimator in an imprecise probability model - Computational aspects and applications
The present article considers estimating a parameter θ in an imprecise probability model (Pθ)θ∈Θ which consists of coherent upper previsions Pθ . After the definition of a...
Robert Hable
VLDB
1999
ACM
159views Database» more  VLDB 1999»
14 years 1 months ago
Aggregation Algorithms for Very Large Compressed Data Warehouses
Many efficient algorithms to compute multidimensional aggregation and Cube for relational OLAP have been developed. However, to our knowledge, there is nothing to date in the lite...
Jianzhong Li, Doron Rotem, Jaideep Srivastava
SDM
2008
SIAM
117views Data Mining» more  SDM 2008»
13 years 10 months ago
A Feature Selection Algorithm Capable of Handling Extremely Large Data Dimensionality
With the advent of high throughput technologies, feature selection has become increasingly important in a wide range of scientific disciplines. We propose a new feature selection ...
Yijun Sun, Sinisa Todorovic, Steve Goodison
COLT
2004
Springer
14 years 2 months ago
An Inequality for Nearly Log-Concave Distributions with Applications to Learning
Abstract— We prove that given a nearly log-concave distribution, in any partition of the space to two well separated sets, the measure of the points that do not belong to these s...
Constantine Caramanis, Shie Mannor