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» Approximation Methods for Supervised Learning
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ECML
2003
Springer
15 years 5 months ago
Pairwise Preference Learning and Ranking
We consider supervised learning of a ranking function, which is a mapping from instances to total orders over a set of labels (options). The training information consists of exampl...
Johannes Fürnkranz, Eyke Hüllermeier
CVPR
2010
IEEE
15 years 9 months ago
Boundary Learning by Optimization with Topological Constraints
Recent studies have shown that machine learning can improve the accuracy of detecting object boundaries in images. In the standard approach, a boundary detector is trained by mini...
Viren Jain, Benjamin Bollmann, Bobby Kasthuri, Ken...
102
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INCDM
2010
Springer
159views Data Mining» more  INCDM 2010»
15 years 5 months ago
Semi-supervised Learning for False Alarm Reduction
Abstract. Intrusion Detection Systems (IDSs) which have been deployed in computer networks to detect a wide variety of attacks are suffering how to manage of a large number of tri...
Chien-Yi Chiu, Yuh-Jye Lee, Chien-Chung Chang, Wen...
ECML
2006
Springer
15 years 4 months ago
Unsupervised Multiple-Instance Learning for Functional Profiling of Genomic Data
Multiple-instance learning (MIL) is a popular concept among the AI community to support supervised learning applications in situations where only incomplete knowledge is available....
Corneliu Henegar, Karine Clément, Jean-Dani...
CVPR
2009
IEEE
16 years 7 months ago
Visual Tracking with Online Multiple Instance Learning
In this paper, we address the problem of learning an adaptive appearance model for object tracking. In particular, a class of tracking techniques called “tracking by detectionâ...
Boris Babenko, Ming-Hsuan Yang, Serge J. Belongie