Sciweavers

Share
10 search results - page 1 / 2
» Approximate computation and implicit regularization for very...
Sort
View
PODS
2012
ACM
240views Database» more  PODS 2012»
6 years 9 months ago
Approximate computation and implicit regularization for very large-scale data analysis
Database theory and database practice are typically the domain of computer scientists who adopt what may be termed an algorithmic perspective on their data. This perspective is ve...
Michael W. Mahoney
ICCS
2003
Springer
8 years 11 months ago
Parallelisation of Sparse Grids for Large Scale Data Analysis
Sparse Grids are the basis for eļ¬ƒcient high dimensional approximation and have recently been applied successfully to predictive modelling. They are spanned by a collection of si...
Jochen Garcke, Markus Hegland, Ole Møller N...
TNN
2008
182views more  TNN 2008»
8 years 6 months ago
Large-Scale Maximum Margin Discriminant Analysis Using Core Vector Machines
Abstract--Large-margin methods, such as support vector machines (SVMs), have been very successful in classification problems. Recently, maximum margin discriminant analysis (MMDA) ...
Ivor Wai-Hung Tsang, András Kocsor, James T...
IPPS
2002
IEEE
8 years 11 months ago
Communication Characteristics of Large-Scale Scientific Applications for Contemporary Cluster Architectures
This paper examines the explicit communication characteristics of several sophisticated scientific applications, which, by themselves, constitute a representative suite of publicl...
Jeffrey S. Vetter, Frank Mueller
NIPS
2007
8 years 7 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
books