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ICCS
2007
Springer
13 years 9 months ago
Adaptive Sparse Grid Classification Using Grid Environments
Common techniques tackling the task of classification in data mining employ ansatz functions associated to training data points to fit the data as well as possible. Instead, the fe...
Dirk Pflüger, Ioan Lucian Muntean, Hans-Joach...
KDD
2009
ACM
198views Data Mining» more  KDD 2009»
14 years 5 months ago
Pervasive parallelism in data mining: dataflow solution to co-clustering large and sparse Netflix data
All Netflix Prize algorithms proposed so far are prohibitively costly for large-scale production systems. In this paper, we describe an efficient dataflow implementation of a coll...
Srivatsava Daruru, Nena M. Marin, Matt Walker, Joy...
GCC
2004
Springer
13 years 10 months ago
Applying Grid Technologies to Distributed Data Mining
The Grid promises improvements in the effectiveness with which global businesses are managed, if it enables distributed expertise to be efficiently applied to the analysis of dist...
Alastair C. Hume, Ashley D. Lloyd, Terence M. Sloa...
IPPS
2007
IEEE
13 years 11 months ago
A Performance Prediction Framework for Grid-Based Data Mining Applications
For a grid middleware to perform resource allocation, prediction models are needed, which can determine how long an application will take for completion on a particular platform o...
Leonid Glimcher, Gagan Agrawal
DATAMINE
1999
140views more  DATAMINE 1999»
13 years 5 months ago
A Scalable Parallel Algorithm for Self-Organizing Maps with Applications to Sparse Data Mining Problems
Abstract. We describe a scalable parallel implementation of the self organizing map (SOM) suitable for datamining applications involving clustering or segmentation against large da...
Richard D. Lawrence, George S. Almasi, Holly E. Ru...