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» A PAC Bound for Approximate Support Vector Machines
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CVPR
2008
IEEE
14 years 9 months ago
A Parallel Decomposition Solver for SVM: Distributed dual ascend using Fenchel Duality
We introduce a distributed algorithm for solving large scale Support Vector Machines (SVM) problems. The algorithm divides the training set into a number of processing nodes each ...
Tamir Hazan, Amit Man, Amnon Shashua
IJCNN
2006
IEEE
14 years 1 months ago
Sparse Optimization for Second Order Kernel Methods
— We present a new optimization procedure which is particularly suited for the solution of second-order kernel methods like e.g. Kernel-PCA. Common to these methods is that there...
Roland Vollgraf, Klaus Obermayer
BMCBI
2010
113views more  BMCBI 2010»
13 years 7 months ago
Prediction of FAD interacting residues in a protein from its primary sequence using evolutionary information
Background: Flavin binding proteins (FBP) plays a critical role in several biological functions such as electron transport system (ETS). These flavoproteins contain very tightly b...
Nitish K. Mishra, Gajendra P. S. Raghava
JMLR
2006
134views more  JMLR 2006»
13 years 7 months ago
Considering Cost Asymmetry in Learning Classifiers
Receiver Operating Characteristic (ROC) curves are a standard way to display the performance of a set of binary classifiers for all feasible ratios of the costs associated with fa...
Francis R. Bach, David Heckerman, Eric Horvitz
ICML
2007
IEEE
14 years 8 months ago
Pegasos: Primal Estimated sub-GrAdient SOlver for SVM
We describe and analyze a simple and effective iterative algorithm for solving the optimization problem cast by Support Vector Machines (SVM). Our method alternates between stocha...
Shai Shalev-Shwartz, Yoram Singer, Nathan Srebro