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https://www.researchgate.net/publication/226519651_Parallel_Randomized_Support_Vector_Machine
A parallel support vector machine based on randomized sampling technique is proposed in this paper. We modeled a new LP-type problem so that it …
https://www.researchgate.net/profile/Vwani_Roychowdhury/publication/220283990_Parallel_randomized_sampling_for_support_vector_machine_SVM_and_support_vector_regression_SVR/links/0c96051e470a90707f000000/Parallel-randomized-sampling-for-support-vector-machine-SVM-and-support-vector-regression-SVR.pdf
Abstract A parallel randomized support vector machine (PRSVM) and a parallel randomized support vector regression (PRSVR) algorithm based on a randomized sampling technique are proposed in this paper.
https://link.springer.com/chapter/10.1007/11731139_25
Abstract. A parallel support vector machine based on randomized sampling technique is proposed in this paper. We modeled a new LP-type problem so that it works for general linear-nonseparable SVM training problems unlike the previous work [2].Cited by: 11
https://link.springer.com/article/10.1007%2Fs10115-007-0082-6
Jun 30, 2007 · A parallel randomized support vector machine (PRSVM) and a parallel randomized support vector regression (PRSVR) algorithm based on a randomized sampling technique are proposed in this paper. The proposed PRSVM and PRSVR have four major advantages over previous methods.Cited by: 12
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.92.781
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): Abstract. A parallel support vector machine based on randomized sampling technique is proposed in this paper. We modeled a new LP-type problem so that it works for general linear-nonseparable SVM training problems unlike the previous work [2]. A unique priority based sampling mechanism is …
https://papers.nips.cc/paper/2608-parallel-support-vector-machines-the-cascade-svm.pdf
implemented on a single processor. Parallel implementations on a cluster of 16 processors were tested with over 1 million vectors (2-class problems), converging in a day or two, while a regular SVM never converged in over a week. 1 Introduction Support Vector Machines [1] are powerful classification and regression tools, but
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://arxiv.org/pdf/1404.1066v1.pdf
plicitly parallel algorithm which is surprisingly efficient, permits a much simpler implementation, and leads to unprecedented speedups in SVM training. 1 Introduction Kernel support vector machines (SVM) are arguably among the most established machine learning algorithms.
http://core.ac.uk/display/24706019
Abstract. Abstract. A parallel support vector machine based on randomized sampling technique is proposed in this paper. We modeled a new LP-type problem so that it works for general linear-nonseparable SVM training problems unlike the previous work [2].Author: Yumao Lu and Vwani Roychowdhury
https://www.ncbi.nlm.nih.gov/pubmed/25045832/
Support Vector Machine models for classification problems were used to validate the total outcomes on bowel well-being. SYNBIO® consumption improved bowel habits of volunteers consuming the probiotic foods or capsules, while the same effects were …Cited by: 5
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