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» Learning of Boolean Functions Using Support Vector Machines
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JMLR
2006
116views more  JMLR 2006»
13 years 9 months ago
Step Size Adaptation in Reproducing Kernel Hilbert Space
This paper presents an online support vector machine (SVM) that uses the stochastic meta-descent (SMD) algorithm to adapt its step size automatically. We formulate the online lear...
S. V. N. Vishwanathan, Nicol N. Schraudolph, Alex ...
AIME
2009
Springer
13 years 6 months ago
Segmentation of Lung Tumours in Positron Emission Tomography Scans: A Machine Learning Approach
Lung cancer represents the most deadly type of malignancy. In this work we propose a machine learning approach to segmenting lung tumours in Positron Emission Tomography (PET) scan...
Aliaksei Kerhet, Cormac Small, Harvey Quon, Terenc...
ICAC
2006
IEEE
14 years 3 months ago
Fast and Effective Worm Fingerprinting via Machine Learning
— As Internet worms become ever faster and more sophisticated, it is important to be able to extract worm signatures in an accurate and timely manner. In this paper, we apply mac...
Stewart M. Yang, Jianping Song, Harish Rajamani, T...
AH
2004
Springer
14 years 2 months ago
Machine Learning Methods for One-Session Ahead Prediction of Accesses to Page Categories
This paper presents a comparison among several well-known machine learning techniques when they are used to carry out a one-session ahead prediction of page categories. We use reco...
José David Martín-Guerrero, Emili Ba...
ALMOB
2008
69views more  ALMOB 2008»
13 years 9 months ago
Learning from positive examples when the negative class is undetermined- microRNA gene identification
Background: The application of machine learning to classification problems that depend only on positive examples is gaining attention in the computational biology community. We an...
Malik Yousef, Segun Jung, Louise C. Showe, Michael...