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CVPR
2008
IEEE
16 years 7 months ago
Mining compositional features for boosting
The selection of weak classifiers is critical to the success of boosting techniques. Poor weak classifiers do not perform better than random guess, thus cannot help decrease the t...
Junsong Yuan, Jiebo Luo, Ying Wu
WWW
2004
ACM
16 years 5 months ago
Mining models of human activities from the web
The ability to determine what day-to-day activity (such as cooking pasta, taking a pill, or watching a video) a person is performing is of interest in many application domains. A ...
Mike Perkowitz, Matthai Philipose, Kenneth P. Fish...
KDD
2009
ACM
159views Data Mining» more  KDD 2009»
16 years 5 months ago
Mining brain region connectivity for alzheimer's disease study via sparse inverse covariance estimation
Effective diagnosis of Alzheimer's disease (AD), the most common type of dementia in elderly patients, is of primary importance in biomedical research. Recent studies have de...
Liang Sun, Rinkal Patel, Jun Liu, Kewei Chen, Tere...
KDD
2008
ACM
148views Data Mining» more  KDD 2008»
16 years 5 months ago
Get another label? improving data quality and data mining using multiple, noisy labelers
This paper addresses the repeated acquisition of labels for data items when the labeling is imperfect. We examine the improvement (or lack thereof) in data quality via repeated la...
Victor S. Sheng, Foster J. Provost, Panagiotis G. ...
KDD
2001
ACM
253views Data Mining» more  KDD 2001»
16 years 5 months ago
GESS: a scalable similarity-join algorithm for mining large data sets in high dimensional spaces
The similarity join is an important operation for mining high-dimensional feature spaces. Given two data sets, the similarity join computes all tuples (x, y) that are within a dis...
Jens-Peter Dittrich, Bernhard Seeger