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» Learning with Rigorous Support Vector Machines
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BMCBI
2007
95views more  BMCBI 2007»
15 years 4 months ago
Phylogenetic tree information aids supervised learning for predicting protein-protein interaction based on distance matrices
Background: Protein-protein interactions are critical for cellular functions. Recently developed computational approaches for predicting protein-protein interactions utilize co-ev...
Roger A. Craig, Li Liao
ISBI
2009
IEEE
15 years 10 months ago
Probabilistic Branching Node Detection Using Hybrid Local Features
Probabilistic branching node inference is an important step for analyzing branching patterns involved in many anatomic structures. We propose combining machine learning techniques...
Haibin Ling, Michael Barnathan, Vasileios Megalooi...
133
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ICIP
2010
IEEE
15 years 1 months ago
Natural DCT statistics approach to no-reference image quality assessment
General-purpose no-reference image quality assessment approaches still lag the advances in full-reference methods. Most no-reference methods are either distortion specific (i.e. t...
Michele A. Saad, Alan C. Bovik, Christophe Charrie...
ICPR
2008
IEEE
16 years 5 months ago
SVMs, Gaussian mixtures, and their generative/discriminative fusion
We present a new technique that employs support vector machines and Gaussian mixture densities to create a generative/discriminative joint classifier. In the past, several approac...
Georg Heigold, Hermann Ney, Thomas Deselaers
WWW
2005
ACM
16 years 4 months ago
Boosting SVM classifiers by ensemble
By far, the support vector machines (SVM) achieve the state-of-theart performance for the text classification (TC) tasks. Due to the complexity of the TC problems, it becomes a ch...
Yan-Shi Dong, Ke-Song Han