Parallelizing Support Vector

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Parallelizing Support Vector Machines for Scalable Image ...

    https://bura.brunel.ac.uk/bitstream/2438/5452/1/FulltextThesis.pdf
    Parallelizing Support Vector Machines for Scalable Image Annotation iii Table of Contents ... N. K. Alham, M. Li, Y. Liu and S. Hammoud, Parallelizing Multiclass Support Vector Machines for Scalable Image Annotation, Neurocomputing, Elsevier Science (under review) ... Parallelizing Support Vector Machines for Scalable Image Annotation 1

Parallelizing Support Vector Machines on Distributed Computers

    http://papers.nips.cc/paper/3202-parallelizing-support-vector-machines-on-distributed-computers.pdf
    PSVM: Parallelizing Support Vector Machines on Distributed Computers Edward Y. Chang⁄, Kaihua Zhu, Hao Wang, Hongjie Bai, Jian Li, Zhihuan Qiu, & Hang Cui Google Research, Beijing, China Abstract Support Vector Machines (SVMs) suffer from a widely recognized scalability problem in both memory use and computational time. To improve scalability,

PSVM: Parallelizing Support Vector Machines on Distributed ...

    https://link.springer.com/chapter/10.1007/978-3-642-20429-6_10
    Aug 26, 2011 · Abstract. 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 loads only essential data to each machine to perform …Cited by: 228

PSVM: Parallelizing Support Vector Machines on Distributed ...

    https://www.researchgate.net/publication/221620344_PSVM_Parallelizing_Support_Vector_Machines_on_Distributed_Computers
    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 by openbigdatagroup - DeepQ Open AI Platform

    http://ai.deepq.com/psvm/
    PSVM Parallelizing Support Vector Machines on Distributed Computers View on GitHub Download .zip Download .tar.gz Introduction. This is the project of the following paper: PSVM: Parallelizing Support Vector Machines on Distributed Computers.It is an all-kernel-support version of SVM, which can parallelly run on multiple machines.

Parallelizing support vector machines for scalable image ...

    https://core.ac.uk/display/337841
    Parallelizing support vector machines for scalable image annotation . By Nasullah Khalid Alham. Abstract. This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Machine learning techniques have facilitated image retrieval by automatically classifying and annotating images with keywords. Among them ...Author: Nasullah Khalid Alham

Parallelizing Support Vector Machines on Distributed Computers

    http://papers.nips.cc/paper/3202-parallelizing-support-vector-machines-on-distributed-computers.pdf
    PSVM: Parallelizing Support Vector Machines on Distributed Computers Edward Y. Chang⁄, Kaihua Zhu, Hao Wang, Hongjie Bai, Jian Li, Zhihuan Qiu, & Hang Cui Google Research, Beijing, China Abstract Support Vector Machines (SVMs) suffer from a widely recognized scalability problem in both memory use and computational time. To improve scalability,

Package ‘parallelSVM’

    https://cran.r-project.org/web/packages/parallelSVM/parallelSVM.pdf
    Package ‘parallelSVM’ ... type Support-Vector-Machine can be used as a classification machine, as a regression machine, or for novelty detection. Depending of whether y is a factor or not, the default setting for type is C-classification or eps-regression, respectively,

Parallelizing Support Vector Machines for Scalable Image ...

    https://bura.brunel.ac.uk/bitstream/2438/5452/1/FulltextThesis.pdf
    Parallelizing Support Vector Machines for Scalable Image Annotation iii Table of Contents ... N. K. Alham, M. Li, Y. Liu and S. Hammoud, Parallelizing Multiclass Support Vector Machines for Scalable Image Annotation, Neurocomputing, Elsevier Science (under review) ... Parallelizing Support Vector Machines for Scalable Image Annotation 1

GitHub - openbigdatagroup/psvm: PSVM: Parallelizing ...

    https://github.com/openbigdatagroup/psvm
    Mar 03, 2016 · If you wish to publish any work based on psvm, please cite our paper as: Edward Chang, Kaihua Zhu, Hao Wang, Hongjie Bai, Jian Li, Zhihuan Qiu, and Hang Cui, PSVM: Parallelizing Support Vector Machines on Distributed Computers.

Parallelizing - definition of Parallelizing by The Free ...

    https://www.thefreedictionary.com/Parallelizing
    Parallelizing synonyms, Parallelizing pronunciation, Parallelizing translation, English dictionary definition of Parallelizing. or vb to draw parallels or points of similarity between Verb 1. parallelize - place parallel to one another lay, place, put, set, position, pose - put into...

PSVM: Parallelizing Support Vector Machines on Distributed ...

    https://www.researchgate.net/publication/221620344_PSVM_Parallelizing_Support_Vector_Machines_on_Distributed_Computers
    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 ...

dblp: Parallelizing Support Vector Machines on Distributed ...

    https://dblp.uni-trier.de/rec/conf/nips/ChangZWBLQC07
    Bibliographic details on Parallelizing Support Vector Machines on Distributed Computers.

Parallelizing support vector machines for scalable image ...

    https://www.researchgate.net/publication/277810151_Parallelizing_support_vector_machines_for_scalable_image_annotation
    Abstract Background Support Vector Machines (SVMs) are used for a growing number,of applications.A fundamental constraint on SVM learning is the management,of the training set.Author: Nasullah Khalid Alham

PSVM: Parallelizing Support Vector Machines on Distributed ...

    https://link.springer.com/chapter/10.1007/978-3-642-20429-6_10
    Aug 26, 2011 · Abstract. 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 loads only essential data to each machine to perform …Cited by: 228

PSVM by openbigdatagroup - DeepQ Open AI Platform

    http://ai.deepq.com/psvm/
    PSVM Parallelizing Support Vector Machines on Distributed Computers View on GitHub Download .zip Download .tar.gz Introduction. This is the project of the following paper: PSVM: Parallelizing Support Vector Machines on Distributed Computers.It is an all-kernel-support version of SVM, which can parallelly run on multiple machines.



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