Будь ласка, використовуйте цей ідентифікатор, щоб цитувати або посилатися на цей матеріал: http://dspace.wunu.edu.ua/handle/316497/30677
Повний запис метаданих
Поле DCЗначенняМова
dc.contributor.authorZhao, Di-
dc.date.accessioned2018-07-18T11:38:03Z-
dc.date.available2018-07-18T11:38:03Z-
dc.date.issued2014-
dc.identifier.citationZhao, D. Fast Solver for Interior Point Method of SVM Training by Parallel GMRES and HSS [Text] / Di Zhao // Computing. - 2014. - Vol. 13, is. 2. - P. 116-124.uk_UA
dc.identifier.urihttp://dspace.tneu.edu.ua/handle/316497/30677-
dc.description.abstractSupport Vector Machine (SVM) is one of the latest statistical models for machine learning. The key problem of SVM training is an optimization problem (mainly Quadratic Programming). Interior Point Method (IPM) is one of mainstream methods to solve Quadratic Programming problem. However, when large-scale dataset is used in IPM based SVM training, computational difficulty happens because of computationally expensive matrix operations. Preconditioner, such as Cholesky factorization (CF), incomplete Cholesky factorization and Kronecker factorization, is an effective approach to decrease time complexity of IPM based SVM training. In this paper, we reformulate SVM training into the saddle point problem. As the research question that motivates this paper, based on parallel GMRES and recently developed preconditioner Hermitian/Skew-Hermitian Separation (HSS), we develop a fast solver HSS- pGMRES-IPM for the saddle point problem from SVM training. Computational results show that, the fast solver HSS- pGMRES-IPM significantly increases the solution speed for the saddle point problem from SVM training than the conventional solver CF.uk_UA
dc.publisherTernopiluk_UA
dc.subjectInterior Point Methoduk_UA
dc.subjectfast solveruk_UA
dc.subjectparallel GMRESuk_UA
dc.subjectHermitian/Skew-Hermitian Separationuk_UA
dc.subjectSupport Vector Machineuk_UA
dc.subjectQuadratic Programminguk_UA
dc.titleFast Solver for Interior Point Method of SVM Training by Parallel GMRES and HSSuk_UA
dc.typeArticleuk_UA
Розташовується у зібраннях:Комп'ютинг 2014 рік. Том 13. Випуск 2

Файли цього матеріалу:
Файл Опис РозмірФормат 
Zhao.pdf349.58 kBAdobe PDFПереглянути/Відкрити


Усі матеріали в архіві електронних ресурсів захищені авторським правом, всі права збережені.