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KDD
2009
ACM
180views Data Mining» more  KDD 2009»
16 years 5 months ago
Using graph-based metrics with empirical risk minimization to speed up active learning on networked data
Active and semi-supervised learning are important techniques when labeled data are scarce. Recently a method was suggested for combining active learning with a semi-supervised lea...
Sofus A. Macskassy
KDD
2009
ACM
156views Data Mining» more  KDD 2009»
16 years 5 months ago
Turning down the noise in the blogosphere
In recent years, the blogosphere has experienced a substantial increase in the number of posts published daily, forcing users to cope with information overload. The task of guidin...
Khalid El-Arini, Gaurav Veda, Dafna Shahaf, Carlos...
KDD
2009
ACM
215views Data Mining» more  KDD 2009»
16 years 5 months ago
Large-scale sparse logistic regression
Logistic Regression is a well-known classification method that has been used widely in many applications of data mining, machine learning, computer vision, and bioinformatics. Spa...
Jun Liu, Jianhui Chen, Jieping Ye
KDD
2009
ACM
188views Data Mining» more  KDD 2009»
16 years 5 months ago
Characteristic relational patterns
Research in relational data mining has two major directions: finding global models of a relational database and the discovery of local relational patterns within a database. While...
Arne Koopman, Arno Siebes
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...
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