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» Informative sampling for large unbalanced data sets
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ESSMAC
2003
Springer
14 years 25 days ago
Filtered Gaussian Processes for Learning with Large Data-Sets
Kernel-based non-parametric models have been applied widely over recent years. However, the associated computational complexity imposes limitations on the applicability of those me...
Jian Qing Shi, Roderick Murray-Smith, D. M. Titter...
TMA
2010
Springer
206views Management» more  TMA 2010»
14 years 2 months ago
Collection and Exploration of Large Data Monitoring Sets Using Bitmap Databases
Collecting and exploring monitoring data is becoming increasingly challenging as networks become larger and faster. Solutions based on both SQL-databases and specialized binary for...
Luca Deri, Valeria Lorenzetti, Steve Mortimer
IV
2005
IEEE
136views Visualization» more  IV 2005»
14 years 1 months ago
Improved Visual Clustering of Large Multi-dimensional Data Sets
Lowering computational cost of data analysis and visualization techniques is an essential step towards including the user in the visualization. In this paper we present an improve...
Eduardo Tejada, Rosane Minghim
ISCI
2002
118views more  ISCI 2002»
13 years 7 months ago
Hyper-rectangle based segmentation and clustering of large video data sets
Video information processing has been one of great challenging areas in the database community since it needs huge amount of storage space and processing power. In this paper, we ...
Seok-Lyong Lee, Chin-Wan Chung
VLDB
2007
ACM
139views Database» more  VLDB 2007»
14 years 1 months ago
A Bayesian Method for Guessing the Extreme Values in a Data Set
For a large number of data management problems, it would be very useful to be able to obtain a few samples from a data set, and to use the samples to guess the largest (or smalles...
Mingxi Wu, Chris Jermaine