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PAMI
2006
147views more  PAMI 2006»
15 years 3 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
AAAI
2008
15 years 5 months ago
Constrained Classification on Structured Data
Most standard learning algorithms, such as Logistic Regression (LR) and the Support Vector Machine (SVM), are designed to deal with i.i.d. (independent and identically distributed...
Chi-Hoon Lee, Matthew R. G. Brown, Russell Greiner...
126
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NIPS
2000
15 years 4 months ago
A New Approximate Maximal Margin Classification Algorithm
A new incremental learning algorithm is described which approximates the maximal margin hyperplane w.r.t. norm p 2 for a set of linearly separable data. Our algorithm, called alm...
Claudio Gentile
ICMLA
2008
15 years 4 months ago
Ensemble Machine Methods for DNA Binding
We introduce three ensemble machine learning methods for analysis of biological DNA binding by transcription factors (TFs). The goal is to identify both TF target genes and their ...
Yue Fan, Mark A. Kon, Charles DeLisi
ICIP
2003
IEEE
16 years 4 months ago
Color photo categorization using compressed histograms and support vector machines
In this paper, an efficient method using various histogrambased (high-dimensional) image content descriptors for automatically classifying general color photos into relevant categ...
Xia Feng, Jianzhong Fang, Guoping Qiu