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» Normalization in Support Vector Machines
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COLT
2003
Springer
15 years 9 months ago
Maximum Margin Algorithms with Boolean Kernels
Recent work has introduced Boolean kernels with which one can learn linear threshold functions over a feature space containing all conjunctions of length up to k (for any 1 ≤ k ...
Roni Khardon, Rocco A. Servedio
EUROPAR
2007
Springer
15 years 10 months ago
Asynchronous Distributed Power Iteration with Gossip-Based Normalization
The dominant eigenvector of matrices defined by weighted links in overlay networks plays an important role in many peer-to-peer applications. Examples include trust management, im...
Márk Jelasity, Geoffrey Canright, Kenth Eng...
BMCBI
2011
14 years 11 months ago
Dynamic programming re-ranking for PPI interactor and pair extraction in full-text articles
Background: Experimentally verified protein-protein interactions (PPIs) cannot be easily retrieved by researchers unless they are stored in PPI databases. The curation of such dat...
Richard Tzong-Han Tsai, Po-Ting Lai
CDC
2009
IEEE
180views Control Systems» more  CDC 2009»
15 years 7 months ago
Robustness analysis for Least Squares kernel based regression: an optimization approach
—In kernel based regression techniques (such as Support Vector Machines or Least Squares Support Vector Machines) it is hard to analyze the influence of perturbed inputs on the ...
Tillmann Falck, Johan A. K. Suykens, Bart De Moor
ECCV
2010
Springer
15 years 5 months ago
Object of Interest Detection by Saliency Learning
In this paper, we present a method for object of interest detection. This method is statistical in nature and hinges in a model which combines salient features using a mixture of l...