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ICCV
2009
IEEE
16 years 11 months ago
Semi-Supervised Random Forests
Random Forests (RFs) have become commonplace in many computer vision applications. Their popularity is mainly driven by their high computational efficiency during both training ...
Christian Leistner, Amir Saffari, Jakob Santner, H...
ICDE
2009
IEEE
158views Database» more  ICDE 2009»
16 years 7 months ago
An Integrated Approach to Performance Monitoring for Autonomous Tuning
With an ever growing complexity and data volume, the administration of today's relational database management systems has become one of the most important cost factors in thei...
Alexander Thiem, Kai-Uwe Sattler
ICIP
2006
IEEE
16 years 7 months ago
On Performance Comparison of Real and Synthetic Iris Images
In the absence of real data for extensive testing of newly designed large-scale biometrics recognition systems a number of solutions are possible including use of resampling metho...
Jinyu Zuo, Natalia A. Schmid, Xiaohan Chen
ICML
2000
IEEE
16 years 7 months ago
FeatureBoost: A Meta-Learning Algorithm that Improves Model Robustness
Most machine learning algorithms are lazy: they extract from the training set the minimum information needed to predict its labels. Unfortunately, this often leads to models that ...
Joseph O'Sullivan, John Langford, Rich Caruana, Av...
KDD
2007
ACM
190views Data Mining» more  KDD 2007»
16 years 6 months ago
Model-shared subspace boosting for multi-label classification
Typical approaches to multi-label classification problem require learning an independent classifier for every label from all the examples and features. This can become a computati...
Rong Yan, Jelena Tesic, John R. Smith