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ECAI
2004
Springer
14 years 29 days ago
Towards Efficient Learning of Neural Network Ensembles from Arbitrarily Large Datasets
Advances in data collection technologies allow accumulation of large and high dimensional datasets and provide opportunities for learning high quality classification and regression...
Kang Peng, Zoran Obradovic, Slobodan Vucetic
IPM
2008
85views more  IPM 2008»
13 years 7 months ago
A new variant of the Pathfinder algorithm to generate large visual science maps in cubic time
In the last few years, there is an increasing interest to generate visual representations of very large scientific domains. A methodology based on the combined use of ISI
Arnaud Quirin, Oscar Cordón, Jose Santamar&...
NIPS
2007
13 years 9 months ago
The Tradeoffs of Large Scale Learning
This contribution develops a theoretical framework that takes into account the effect of approximate optimization on learning algorithms. The analysis shows distinct tradeoffs for...
Léon Bottou, Olivier Bousquet
ESSMAC
2003
Springer
14 years 24 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...
VIS
2004
IEEE
134views Visualization» more  VIS 2004»
14 years 8 months ago
Hierarchy Based 3D Visualization of Large Software Structures
Modern object-oriented programs are hierarchical systems with many thousands of interrelated subsystems. Visualization helps developers to better comprehend these large and comple...
Michael Balzer, Oliver Deussen