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» Learning of Boolean Functions Using Support Vector Machines
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ICML
2005
IEEE
14 years 10 months ago
Supervised dimensionality reduction using mixture models
Given a classification problem, our goal is to find a low-dimensional linear transformation of the feature vectors which retains information needed to predict the class labels. We...
Sajama, Alon Orlitsky
ALT
2006
Springer
14 years 6 months ago
Large-Margin Thresholded Ensembles for Ordinal Regression: Theory and Practice
Abstract. We propose a thresholded ensemble model for ordinal regression problems. The model consists of a weighted ensemble of confidence functions and an ordered vector of thres...
Hsuan-Tien Lin, Ling Li
ICC
2007
IEEE
141views Communications» more  ICC 2007»
14 years 3 months ago
A Hybrid Model to Detect Malicious Executables
— We present a hybrid data mining approach to detect malicious executables. In this approach we identify important features of the malicious and benign executables. These feature...
Mohammad M. Masud, Latifur Khan, Bhavani M. Thurai...
BIOINFORMATICS
2005
140views more  BIOINFORMATICS 2005»
13 years 9 months ago
Profile-based direct kernels for remote homology detection and fold recognition
Motivation: Remote homology detection between protein sequences is a central problem in computational biology. Supervised learning algorithms based on support vector machines are ...
Huzefa Rangwala, George Karypis
MICCAI
2000
Springer
14 years 21 days ago
Small Sample Size Learning for Shape Analysis of Anatomical Structures
We present a novel approach to statistical shape analysis of anatomical structures based on small sample size learning techniques. The high complexity of shape models used in medic...
Polina Golland, W. Eric L. Grimson, Martha Elizabe...