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» Forecasting high-dimensional data
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ICDE
2008
IEEE
150views Database» more  ICDE 2008»
15 years 11 months ago
On the Anonymization of Sparse High-Dimensional Data
Abstract-- Existing research on privacy-preserving data publishing focuses on relational data: in this context, the objective is to enforce privacy-preserving paradigms, such as ka...
Gabriel Ghinita, Yufei Tao, Panos Kalnis
CSB
2003
IEEE
150views Bioinformatics» more  CSB 2003»
15 years 2 months ago
Algorithms for Bounded-Error Correlation of High Dimensional Data in Microarray Experiments
The problem of clustering continuous valued data has been well studied in literature. Its application to microarray analysis relies on such algorithms as -means, dimensionality re...
Mehmet Koyutürk, Ananth Grama, Wojciech Szpan...
ICANN
2009
Springer
15 years 2 months ago
Empirical Study of the Universum SVM Learning for High-Dimensional Data
Abstract. Many applications of machine learning involve sparse highdimensional data, where the number of input features is (much) larger than the number of data samples, d n. Predi...
Vladimir Cherkassky, Wuyang Dai
IADIS
2008
14 years 11 months ago
Mib: Using Mutual Information for Biclustering High Dimensional Data
Most of the biclustering algorithms for gene expression data are based either on the Euclidean distance or correlation coefficient which capture only linear relationships. However...
Neelima Gupta, Seema Aggarwal