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TMI
2010
172views more  TMI 2010»
13 years 9 months ago
Comparison of AdaBoost and Support Vector Machines for Detecting Alzheimer's Disease Through Automated Hippocampal Segmentation
Abstract— We compared four automated methods for hippocampal segmentation using different machine learning algorithms (1) hierarchical AdaBoost, (2) Support Vector Machines (SVM)...
Jonathan H. Morra, Zhuowen Tu, Liana G. Apostolova...
KDD
2009
ACM
215views Data Mining» more  KDD 2009»
14 years 11 months ago
Large-scale sparse logistic regression
Logistic Regression is a well-known classification method that has been used widely in many applications of data mining, machine learning, computer vision, and bioinformatics. Spa...
Jun Liu, Jianhui Chen, Jieping Ye
ICCV
2005
IEEE
14 years 4 months ago
Perceptual Scale Space and its Applications
When an image is viewed at varying resolutions, it is known to create discrete perceptual jumps or transitions amid the continuous intensity changes. In this paper, we study a per...
Yizhou Wang, Siavosh Bahrami, Song Chun Zhu
ECML
2005
Springer
14 years 4 months ago
Kernel Basis Pursuit
ABSTRACT. Estimating a non-uniformly sampled function from a set of learning points is a classical regression problem. Kernel methods have been widely used in this context, but eve...
Vincent Guigue, Alain Rakotomamonjy, Stépha...
GECCO
2007
Springer
212views Optimization» more  GECCO 2007»
14 years 2 months ago
Controlling overfitting with multi-objective support vector machines
Recently, evolutionary computation has been successfully integrated into statistical learning methods. A Support Vector Machine (SVM) using evolution strategies for its optimizati...
Ingo Mierswa