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ISCI
2008
116views more  ISCI 2008»
13 years 7 months ago
Discovery of maximum length frequent itemsets
The use of frequent itemsets has been limited by the high computational cost as well as the large number of resulting itemsets. In many real-world scenarios, however, it is often ...
Tianming Hu, Sam Yuan Sung, Hui Xiong, Qian Fu
ADMA
2006
Springer
110views Data Mining» more  ADMA 2006»
13 years 11 months ago
Learning with Local Drift Detection
Abstract. Most of the work in Machine Learning assume that examples are generated at random according to some stationary probability distribution. In this work we study the problem...
João Gama, Gladys Castillo
KDD
2008
ACM
199views Data Mining» more  KDD 2008»
14 years 8 months ago
Building semantic kernels for text classification using wikipedia
Document classification presents difficult challenges due to the sparsity and the high dimensionality of text data, and to the complex semantics of the natural language. The tradi...
Pu Wang, Carlotta Domeniconi
SDM
2007
SIAM
162views Data Mining» more  SDM 2007»
13 years 9 months ago
Probabilistic Joint Feature Selection for Multi-task Learning
We study the joint feature selection problem when learning multiple related classification or regression tasks. By imposing an automatic relevance determination prior on the hypo...
Tao Xiong, Jinbo Bi, R. Bharat Rao, Vladimir Cherk...
CSDA
2007
99views more  CSDA 2007»
13 years 7 months ago
CLUES: A non-parametric clustering method based on local shrinking
In this paper, we propose a novel non-parametric clustering method based on non-parametric local shrinking. Each data point is transformed in such a way that it moves a specific ...
Xiaogang Wang, Weiliang Qiu, Ruben H. Zamar