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PAMI
2006
147views more  PAMI 2006»
14 years 10 months ago
Bayesian Gaussian Process Classification with the EM-EP Algorithm
Gaussian process classifiers (GPCs) are Bayesian probabilistic kernel classifiers. In GPCs, the probability of belonging to a certain class at an input location is monotonically re...
Hyun-Chul Kim, Zoubin Ghahramani
TNN
2008
182views more  TNN 2008»
14 years 9 months ago
Large-Scale Maximum Margin Discriminant Analysis Using Core Vector Machines
Abstract--Large-margin methods, such as support vector machines (SVMs), have been very successful in classification problems. Recently, maximum margin discriminant analysis (MMDA) ...
Ivor Wai-Hung Tsang, András Kocsor, James T...
CVPR
2012
IEEE
13 years 12 days ago
Spatial bias in multi-atlas based segmentation
Multi-atlas segmentation has been widely applied in medical image analysis. With deformable registration, this technique realizes label transfer from pre-labeled atlases to unknow...
Hongzhi Wang, Paul A. Yushkevich
KDD
2007
ACM
168views Data Mining» more  KDD 2007»
15 years 10 months ago
Detecting time series motifs under uniform scaling
Time series motifs are approximately repeated patterns found within the data. Such motifs have utility for many data mining algorithms, including rule-discovery, novelty-detection...
Dragomir Yankov, Eamonn J. Keogh, Jose Medina, Bil...
ICML
2009
IEEE
15 years 10 months ago
Optimal reverse prediction: a unified perspective on supervised, unsupervised and semi-supervised learning
Training principles for unsupervised learning are often derived from motivations that appear to be independent of supervised learning. In this paper we present a simple unificatio...
Linli Xu, Martha White, Dale Schuurmans