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EMO
2009
Springer
147views Optimization» more  EMO 2009»
16 years 11 days ago
Application of MOGA Search Strategy to SVM Training Data Selection
When training Support Vector Machine (SVM), selection of a training data set becomes an important issue, since the problem of overfitting exists with a large number of training da...
Tomoyuki Hiroyasu, Masashi Nishioka, Mitsunori Mik...
ICPR
2008
IEEE
16 years 7 days ago
A fast revised simplex method for SVM training
Active set methods for training the Support Vector Machines (SVM) are advantageous since they enable incremental training and, as we show in this research, do not exhibit exponent...
Christopher Sentelle, Georgios C. Anagnostopoulos,...
ICRA
2008
IEEE
137views Robotics» more  ICRA 2008»
16 years 7 days ago
SVM-based discriminative accumulation scheme for place recognition
— Integrating information coming from different sensors is a fundamental capability for autonomous robots. For complex tasks like topological localization, it would be desirable ...
Andrzej Pronobis, Óscar Martínez Moz...
133
Voted
ICC
2007
IEEE
132views Communications» more  ICC 2007»
16 years 3 days ago
Quarter Sphere Based Distributed Anomaly Detection in Wireless Sensor Networks
—Anomaly detection is an important challenge for tasks such as fault diagnosis and intrusion detection in energy constrained wireless sensor networks. A key problem is how to min...
Sutharshan Rajasegarar, Christopher Leckie, Marimu...
CVPR
2010
IEEE
15 years 10 months ago
An Efficient Divide-and-Conquer Cascade for Nonlinear Object Detection
We introduce a method to accelerate the evaluation of object detection cascades with the help of a divide-andconquer procedure in the space of candidate regions. Compared to the e...
Christoph Lampert