77 search results - page 10 / 16 » On the Anonymization of Sparse High-Dimensional Data |
ICML
2009
IEEE
14 years 7 months ago
2009
IEEE
Sparsity is a desirable property in high dimensional learning. The 1-norm regularization can lead to primal sparsity, while max-margin methods achieve dual sparsity. Combining the...
DATAMINE
2007
13 years 6 months ago
2007
The high dimensionality of massive data results in the discovery of a large number of association rules. The huge number of rules makes it difficult to interpret and react to all ...
SC
2009
ACM
13 years 11 months ago
2009
ACM
It has been shown that the sparse grid combination technique can be a practical tool to solve high dimensional PDEs arising in multidimensional option pricing problems in finance...
BMCBI
2007
2007
Penalized likelihood for sparse contingency tables with an application to full-length cDNA libraries
13 years 6 months ago
Background: The joint analysis of several categorical variables is a common task in many areas of biology, and is becoming central to systems biology investigations whose goal is ...
SADM
2010
13 years 1 months ago
2010
This paper is concerned with classifying high dimensional data into one of two categories. In various settings, such as when dealing with fMRI and microarray data, the number of v...