Parallelizing Support Vector Machines On

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Parallelizing Support Vector Machines on Distributed Computers

    https://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,

Parallelizing Support Vector Machines for Scalable Image ...

    https://bura.brunel.ac.uk/bitstream/2438/5452/1/FulltextThesis.pdf
    Nasullah Khalid Alham (2011) Parallelizing Support Vector Machines for Scalable Image Annotation ii Abstract Machine learning techniques have facilitated image retrieval by automatically classifying and

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 ...

1.4. Support Vector Machines — scikit-learn 0.22.1 ...

    https://scikit-learn.org/stable/modules/svm.html
    The support vector machines in scikit-learn support both dense (numpy.ndarray and convertible to that by numpy.asarray) and sparse (any scipy.sparse) sample vectors as input. However, to use an SVM to make predictions for sparse data, it must have been fit on such data.

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, ... package in R 2.14.0, provides functions for parallel execution of R code on machines with multiple cores or processors, using the system fork call ...

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.

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

CiteSeerX — PSVM: Parallelizing Support Vector Machines on ...

    http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.143.7569
    CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): 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 ...

Parallelizing Support Vector Machines on Distributed ...

    https://research.google/pubs/pub34638/
    We maintain a portfolio of research projects, providing individuals and teams the freedom to emphasize specific types of workCited by: 228



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