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KDD
2004
ACM
187views Data Mining» more  KDD 2004»
16 years 6 months ago
IMMC: incremental maximum margin criterion
Subspace learning approaches have attracted much attention in academia recently. However, the classical batch algorithms no longer satisfy the applications on streaming data or la...
Jun Yan, Benyu Zhang, Shuicheng Yan, Qiang Yang, H...
KDD
2003
ACM
124views Data Mining» more  KDD 2003»
16 years 6 months ago
Information-theoretic co-clustering
Two-dimensional contingency or co-occurrence tables arise frequently in important applications such as text, web-log and market-basket data analysis. A basic problem in contingenc...
Inderjit S. Dhillon, Subramanyam Mallela, Dharmend...
ICDM
2006
IEEE
119views Data Mining» more  ICDM 2006»
15 years 11 months ago
Fast On-line Kernel Learning for Trees
Kernel methods have been shown to be very effective for applications requiring the modeling of structured objects. However kernels for structures usually are too computational dem...
Fabio Aiolli, Giovanni Da San Martino, Alessandro ...
PKDD
1999
Springer
272views Data Mining» more  PKDD 1999»
15 years 10 months ago
Handling Missing Data in Trees: Surrogate Splits or Statistical Imputation
Abstract. In many applications of data mining a - sometimes considerable - part of the data values is missing. This may occur because the data values were simply never entered into...
A. J. Feelders
DAWAK
2005
Springer
15 years 11 months ago
DWEB: A Data Warehouse Engineering Benchmark
Abstract. Data warehouse architectural choices and optimization techniques are critical to decision support query performance. To facilitate these choices, the performance of the d...
Jérôme Darmont, Omar Boussaid, Fadila...