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» Learning with Rigorous Support Vector Machines
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BMCBI
2006
180views more  BMCBI 2006»
14 years 12 months ago
Building multiclass classifiers for remote homology detection and fold recognition
Motivation Protein remote homology prediction and fold recognition are central problems in computational biology. Supervised learning algorithms based on support vector machines a...
Huzefa Rangwala, George Karypis
PAMI
2006
147views more  PAMI 2006»
14 years 11 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
SMC
2010
IEEE
132views Control Systems» more  SMC 2010»
14 years 10 months ago
Selection of SIFT feature points for scene description in robot vision
This paper presents a method for selection of SIFT(Scale-Invariant Feature Transform) feature points using OC-SVM (One Class-Support Vector Machines). We proposed the method for au...
Yuya Utsumi, Masahiro Tsukada, Hirokazu Madokoro, ...
KDD
2006
ACM
179views Data Mining» more  KDD 2006»
16 years 7 days ago
Extracting key-substring-group features for text classification
In many text classification applications, it is appealing to take every document as a string of characters rather than a bag of words. Previous research studies in this area mostl...
Dell Zhang, Wee Sun Lee
ML
2008
ACM
248views Machine Learning» more  ML 2008»
14 years 11 months ago
Feature selection via sensitivity analysis of SVM probabilistic outputs
Feature selection is an important aspect of solving data-mining and machine-learning problems. This paper proposes a feature-selection method for the Support Vector Machine (SVM) l...
Kai Quan Shen, Chong Jin Ong, Xiao Ping Li, Einar ...