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» Learning of Boolean Functions Using Support Vector Machines
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BMCBI
2006
85views more  BMCBI 2006»
13 years 9 months ago
Searching for interpretable rules for disease mutations: a simulated annealing bump hunting strategy
Background: Understanding how amino acid substitutions affect protein functions is critical for the study of proteins and their implications in diseases. Although methods have bee...
Rui Jiang, Hua Yang, Fengzhu Sun, Ting Chen
CVPR
2010
IEEE
14 years 1 months ago
An Efficient Divide-and-Conquer Cascade for Nonlinear Object Detection
We introduce a method to accelerate the evaluation of object detection cascades with the help of a divide-andconquer procedure in the space of candidate regions. Compared to the e...
Christoph Lampert
SDM
2011
SIAM
232views Data Mining» more  SDM 2011»
13 years 3 days ago
A Sequential Dual Method for Structural SVMs
In many real world prediction problems the output is a structured object like a sequence or a tree or a graph. Such problems range from natural language processing to computationa...
Shirish Krishnaj Shevade, Balamurugan P., S. Sunda...
ICASSP
2011
IEEE
13 years 1 months ago
Online Kernel SVM for real-time fMRI brain state prediction
The Support Vector Machine (SVM) methodology is an effective, supervised, machine learning method that gives stateof-the-art performance for brain state classification from funct...
Yongxin Taylor Xi, Hao Xu, Ray Lee, Peter J. Ramad...
BMCBI
2007
121views more  BMCBI 2007»
13 years 9 months ago
Predicting zinc binding at the proteome level
Background: Metalloproteins are proteins capable of binding one or more metal ions, which may be required for their biological function, for regulation of their activities or for ...
Andrea Passerini, Claudia Andreini, Sauro Menchett...