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» Dynamically Adapting Kernels in Support Vector Machines
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KDD
2004
ACM
117views Data Mining» more  KDD 2004»
16 years 4 months ago
Regularized multi--task learning
Past empirical work has shown that learning multiple related tasks from data simultaneously can be advantageous in terms of predictive performance relative to learning these tasks...
Theodoros Evgeniou, Massimiliano Pontil
146
Voted
ICRA
2008
IEEE
134views Robotics» more  ICRA 2008»
15 years 10 months ago
Towards robust place recognition for robot localization
— Localization and context interpretation are two key competences for mobile robot systems. Visual place recognition, as opposed to purely geometrical models, holds promise of hi...
Muhammad Muneeb Ullah, Andrzej Pronobis, Barbara C...
CONEXT
2007
ACM
15 years 5 months ago
Detecting worm variants using machine learning
Network intrusion detection systems typically detect worms by examining packet or flow logs for known signatures. Not only does this approach mean worms cannot be detected until ...
Oliver Sharma, Mark Girolami, Joseph S. Sventek
111
Voted
JCP
2006
78views more  JCP 2006»
15 years 3 months ago
Parameter Optimization of Kernel-based One-class Classifier on Imbalance Learning
Compared with conventional two-class learning schemes, one-class classification simply uses a single class in the classifier training phase. Applying one-class classification to le...
Ling Zhuang, Honghua Dai
ICPR
2010
IEEE
15 years 1 months ago
Low-Level Image Segmentation Based Scene Classification
This paper is aimed at evaluating the semantic information content of multiscale, low-level image segmentation. As a method of doing this, we use selected features of segmentation...
Emre Akbas, Narendra Ahuja