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https://www.researchgate.net/publication/3303738_Distributed_Support_Vector_Machines
With a large number of sensors and control units in networked systems, distributed support vector machines (DSVMs) play a fundamental role in scalable and efficient multi-sensor classification and ...
https://www2.eecs.berkeley.edu/Pubs/TechRpts/2015/EECS-2015-9.pdf
implement communication-efficient versions of parallel support vector machines, a widely used classifier in statistical machine learning, for distributed memory clusters and supercomputers. The main computational bottleneck is the training phase, in which a statistical model …
http://papers.nips.cc/paper/3202-parallelizing-support-vector-machines-on-distributed-computers.pdf
Support Vector Machines (SVMs) suffer from a widely recognized scalability problem in both memory use and computational time. To improve scalability, we have developed a parallel SVM algorithm (PSVM), which reduces memory use through performing a row-based, approximate matrix factorization, and which
https://scholarworks.uno.edu/cgi/viewcontent.cgi?article=1711&context=td
Distributed Support Vector Machine Learning A Thesis Submitted to the Graduate Faculty of the University of New Orleans in partial fulfillment of the requirements for the degree of Master of Science in Computer Science Bioinformatics by Kenneth C. Armond …Author: Armond, C Kenneth
http://thesiddharth.github.io/dpsvm/
WRITE-UP Summary. We have implemented a distributed and parallel Support Vector Machine training algorithm for binary classification using the OpenMPI library and the CUDA parallel programming model. Our implementation achieves the same accuracy as the ubiquitously used SVM solver LibSVM on 4 popular datasets, with speedups of up to 300x against the latter, and up to 10x against a few of the ...
https://ieeexplore.ieee.org/document/4470008/
Abstract: In this paper, we propose a distributed parallel support vector machine (DPSVM) training mechanism in a configurable network environment for distributed data mining. The basic idea is to exchange support vectors among a strongly connected network (SCN) so that multiple servers may work concurrently on distributed data set with limited communication cost and fast training speed.Cited by: 118
https://www.cc.gatech.edu/~lsong/papers/YouDemCzeSonVud15.pdf
CA-SVM: Communication-Avoiding Parallel Support Vector Machines on Distributed Systems Yang Youzy, James Demmely, Kenneth Czechowski, Le Song, Richard Vuduc zDepartment of Computer Science and Technology, Tsinghua University, Beijing, China yComputer Science Division, University of California at Berkeley, Berkeley, CA, USA College of Computing, Georgia Institute of Technology, …
https://arxiv.org/pdf/1811.11922
This paper studies distributed inference for linear support vector machine (SVM) for the binary classi cation task. Despite a vast literature on SVM, much less is known about the inferential properties of SVM, especially in a distributed setting. In this paper, we pro-pose a multi-round distributed linear-type (MDL) estimator for conductingCited by: 3
https://ieeexplore.ieee.org/xpl/aboutJournal.jsp?punumber=71
IEEE Transactions on Parallel and Distributed Systems (TPDS) is published monthly. It publishes a range of papers, comments on previously published papers, and survey articles that deal with the parallel and distributed systems research areas of current importance to our readers. The articles in this journal are peer reviewed in accordance with the requirements set forth in the IEEE PSPB ...
https://www.dtc.umn.edu/s/resources/jmlr2010.pdf
CONSENSUS-BASED DISTRIBUTED SUPPORT VECTOR MACHINES to a classifier trained using the data of nodes that remain operational. But ev en if the net-work becomes disconnected, the proposed algorithm will stay operational with performance
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