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» A supervised learning approach for imbalanced data sets
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IJCAI
2007
15 years 5 months ago
A Fully Connectionist Model Generator for Covered First-Order Logic Programs
We present a fully connectionist system for the learning of first-order logic programs and the generation of corresponding models: Given a program and a set of training examples,...
Sebastian Bader, Pascal Hitzler, Steffen Höll...
CVPR
2007
IEEE
16 years 6 months ago
Feature Mining for Image Classification
The efficiency and robustness of a vision system is often largely determined by the quality of the image features available to it. In data mining, one typically works with immense...
Piotr Dollár, Zhuowen Tu, Hai Tao, Serge Be...
ICIP
2008
IEEE
16 years 6 months ago
Emotional valence categorization using holistic image features
Can a machine learn to perceive emotions as evoked by an artwork? Here we propose an emotion categorization system, trained by ground truth from psychology studies. The training d...
Victoria Yanulevskaya, Jan van Gemert, Katharina R...
AAAI
2000
15 years 5 months ago
Selective Sampling with Redundant Views
Selective sampling, a form of active learning, reduces the cost of labeling training data by asking only for the labels of the most informative unlabeled examples. We introduce a ...
Ion Muslea, Steven Minton, Craig A. Knoblock
ICML
2007
IEEE
16 years 5 months ago
Simpler core vector machines with enclosing balls
The core vector machine (CVM) is a recent approach for scaling up kernel methods based on the notion of minimum enclosing ball (MEB). Though conceptually simple, an efficient impl...
András Kocsor, Ivor W. Tsang, James T. Kwok