TY - GEN
T1 - A parallel decomposition solver for SVM
T2 - 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR
AU - Hazan, Tamir
AU - Man, Amit
AU - Shashua, Amnon
PY - 2008
Y1 - 2008
N2 - 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 running independently an SVM sub-problem associated with its subset of training data. The algorithm is a parallel (Jacobi) block-update scheme derived from the convex conjugate (Fenchel Duality) form of the original SVM problem. Each update step consists of a modified SVM solver running in parallel over the sub-problems followed by a simple global update. We derive bounds on the number of updates showing that the number of iterations (independent SVM applications on sub-problems) required to obtain a solution of accuracy ε is O(log(1/ε)). We demonstrate the efficiency and applicability of our algorithms by running on large scale experiments on standardized datasets while comparing the results to the state-of-the-art SVM solvers.
AB - 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 running independently an SVM sub-problem associated with its subset of training data. The algorithm is a parallel (Jacobi) block-update scheme derived from the convex conjugate (Fenchel Duality) form of the original SVM problem. Each update step consists of a modified SVM solver running in parallel over the sub-problems followed by a simple global update. We derive bounds on the number of updates showing that the number of iterations (independent SVM applications on sub-problems) required to obtain a solution of accuracy ε is O(log(1/ε)). We demonstrate the efficiency and applicability of our algorithms by running on large scale experiments on standardized datasets while comparing the results to the state-of-the-art SVM solvers.
UR - http://www.scopus.com/inward/record.url?scp=52249111632&partnerID=8YFLogxK
U2 - 10.1109/CVPR.2008.4587354
DO - 10.1109/CVPR.2008.4587354
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AN - SCOPUS:52249111632
SN - 9781424422432
T3 - 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR
BT - 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR
Y2 - 23 June 2008 through 28 June 2008
ER -