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SADM
2011
13 years 1 months ago
Random survival forests for high-dimensional data
: Minimal depth is a dimensionless order statistic that measures the predictiveness of a variable in a survival tree. It can be used to select variables in high-dimensional problem...
Hemant Ishwaran, Udaya B. Kogalur, Xi Chen, Andy J...
IVC
2011
190views more  IVC 2011»
13 years 1 months ago
A graphical model based solution to the facial feature point tracking problem
In this paper a facial feature point tracker that is motivated by applications such as human-computer interfaces and facial expression analysis systems is proposed. The proposed t...
Serhan Cosar, Müjdat Çetin
JCS
2000
148views more  JCS 2000»
13 years 6 months ago
Using Sample Size to Limit Exposure to Data Mining
Data mining introduces new problems in database security. The basic problem of using non-sensitive data to infer sensitive data is made more difficult by the "prob abilistic&...
Chris Clifton
VISSYM
2004
13 years 7 months ago
Shape-Embedded-Histograms for Visual Data Mining
Scatterplots are widely used in exploratory data analysis and class visualization. The advantages of scatterplots are that they are easy to understand and allow the user to draw c...
Amihood Amir, Reuven Kashi, Daniel A. Keim, Nathan...
DAMON
2009
Springer
14 years 27 days ago
Frequent itemset mining on graphics processors
We present two efficient Apriori implementations of Frequent Itemset Mining (FIM) that utilize new-generation graphics processing units (GPUs). Our implementations take advantage ...
Wenbin Fang, Mian Lu, Xiangye Xiao, Bingsheng He, ...