171 search results - page 13 / 35 » A Boosting Approach to Multiple Instance Learning |
KAIS
2010
13 years 6 months ago
2010
Real world data mining applications must address the issue of learning from imbalanced data sets. The problem occurs when the number of instances in one class greatly outnumbers t...
ECCV
2010
Springer
14 years 1 months ago
2010
Springer
Many learning tasks for computer vision problems can be described by multiple views or multiple features. These views can be exploited in order to learn from unlabeled data, a.k.a....
ICDM
2009
IEEE
13 years 5 months ago
2009
IEEE
Anomaly detection is an important data mining task. Most existing methods treat anomalies as inconsistencies and spend the majority amount of time on modeling normal instances. A r...
KDD
2007
ACM
14 years 8 months ago
2007
ACM
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...
CIKM
2008
Springer
13 years 9 months ago
2008
Springer
Proactive learning is a generalization of active learning designed to relax unrealistic assumptions and thereby reach practical applications. Active learning seeks to select the m...