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» Approximate data mining in very large relational data
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KDD
2008
ACM
167views Data Mining» more  KDD 2008»
16 years 2 months ago
A sequential dual method for large scale multi-class linear svms
Efficient training of direct multi-class formulations of linear Support Vector Machines is very useful in applications such as text classification with a huge number examples as w...
S. Sathiya Keerthi, S. Sundararajan, Kai-Wei Chang...
KAIS
2006
164views more  KAIS 2006»
15 years 1 months ago
On efficiently summarizing categorical databases
Frequent itemset mining was initially proposed and has been studied extensively in the context of association rule mining. In recent years, several studies have also extended its a...
Jianyong Wang, George Karypis
IDA
2002
Springer
15 years 1 months ago
Classification with sparse grids using simplicial basis functions
Recently we presented a new approach [20] to the classification problem arising in data mining. It is based on the regularization network approach but in contrast to other methods...
Jochen Garcke, Michael Griebel
PAKDD
2009
ACM
149views Data Mining» more  PAKDD 2009»
15 years 6 months ago
A New Local Distance-Based Outlier Detection Approach for Scattered Real-World Data
Detecting outliers which are grossly different from or inconsistent with the remaining dataset is a major challenge in real-world KDD applications. Existing outlier detection met...
Ke Zhang, Marcus Hutter, Huidong Jin
PPSC
1993
15 years 3 months ago
Parallel Preconditioning and Approximate Inverses on the Connection Machine
We present a new approach to preconditioning for very large, sparse, non-symmetric, linear systems. We explicitly compute an approximate inverse to our original matrix that can be...
Marcus J. Grote, Horst D. Simon