{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T00:52:28Z","timestamp":1740099148982,"version":"3.37.3"},"publisher-location":"Cham","reference-count":18,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319971353"},{"type":"electronic","value":"9783319971360"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-3-319-97136-0_9","type":"book-chapter","created":{"date-parts":[[2018,7,16]],"date-time":"2018-07-16T09:33:12Z","timestamp":1531733592000},"page":"115-129","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Investigating Convergence of Linear SVM Implemented in PermonSVM Employing MPRGP Algorithm"],"prefix":"10.1007","author":[{"given":"Jakub","family":"Kru\u017e\u00edk","sequence":"first","affiliation":[]},{"given":"Marek","family":"Pecha","sequence":"additional","affiliation":[]},{"given":"V\u00e1clav","family":"Hapla","sequence":"additional","affiliation":[]},{"given":"David","family":"Hor\u00e1k","sequence":"additional","affiliation":[]},{"given":"Martin","family":"\u010cerm\u00e1k","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,7,17]]},"reference":[{"key":"9_CR1","unstructured":"ExCAPE: exascale compound activity prediction. http:\/\/www.excape-h2020.eu"},{"key":"9_CR2","unstructured":"LIBSVM data: classification, regression, and multi-label. https:\/\/www.csie.ntu.edu.tw\/~cjlin\/libsvmtools\/datasets\/"},{"key":"9_CR3","unstructured":"IT4Innovations: Salomon cluster documentation - hardware overview. National Supercomputing Center, VSB-Technical University of Ostrava (2017). https:\/\/docs.it4i.cz\/salomon-cluster-documentation\/hardware-overview"},{"key":"9_CR4","unstructured":"Balay, S., Abhyankar, S., Adams, M.F., Brown, J., Brune, P., Buschelman, K., Eijkhout, V., Gropp, W.D., Kaushik, D., Knepley, M.G., McInnes, L.C., Rupp, K., Smith, B.F., Zhang, H.: PETSc - Portable, Extensible Toolkit for Scientific Computation. http:\/\/www.mcs.anl.gov\/petsc"},{"issue":"1","key":"9_CR5","doi-asserted-by":"publisher","first-page":"262","DOI":"10.1073\/pnas.97.1.262","volume":"97","author":"M Brown","year":"2000","unstructured":"Brown, M., Grundy, W., Lin, D., Cristianini, N., Sugnet, C., Furey, T., Ares Jr., M., Haussler, D.: Knowledge-based analysis of microarray gene expression data by using support vector machines. Proc. Nat. Acad. Sci. U.S.A. 97(1), 262\u2013267 (2000)","journal-title":"Proc. Nat. Acad. Sci. U.S.A."},{"key":"9_CR6","doi-asserted-by":"publisher","DOI":"10.1002\/9780470140529","volume-title":"Learning from Data: Concepts, Theory, and Methods","author":"V Cherkassky","year":"2007","unstructured":"Cherkassky, V., Mulier, F.M.: Learning from Data: Concepts, Theory, and Methods. Wiley-IEEE Press, Hoboken (2007)"},{"issue":"3","key":"9_CR7","first-page":"273","volume":"20","author":"C Cortes","year":"1995","unstructured":"Cortes, C., Vapnik, V.: Support-vector networks. Mach. Learn. 20(3), 273\u2013297 (1995)","journal-title":"Mach. Learn."},{"key":"9_CR8","series-title":"SOIA","doi-asserted-by":"publisher","DOI":"10.1007\/b138610","volume-title":"Optimal Quadratic Programming Algorithms, with Applications to Variational Inequalities","author":"Z Dost\u00e1l","year":"2009","unstructured":"Dost\u00e1l, Z.: Optimal Quadratic Programming Algorithms, with Applications to Variational Inequalities. SOIA, vol. 23. Springer, New York (2009). https:\/\/doi.org\/10.1007\/b138610"},{"issue":"2","key":"9_CR9","doi-asserted-by":"publisher","first-page":"179","DOI":"10.1016\/j.rse.2006.04.001","volume":"103","author":"GM Foody","year":"2006","unstructured":"Foody, G.M., Mathur, A.: The use of small training sets containing mixed pixels for accurate hard image classification: training on mixed spectral responses for classification by a SVM. Remote Sens. Environ. 103(2), 179\u2013189 (2006)","journal-title":"Remote Sens. Environ."},{"key":"9_CR10","unstructured":"Hapla, V., Hor\u00e1k, D., Pecha, M.: PermonSVM (2017). http:\/\/permon.it4i.cz\/permonsvm.htm"},{"key":"9_CR11","unstructured":"Hapla, V., Hor\u00e1k, D., \u010cerm\u00e1k, M., Kru\u017e\u00edk, J., Posp\u00ed\u0161il, L., Sojka, R.: PermonQP (2015). http:\/\/permon.it4i.cz\/qp\/"},{"key":"9_CR12","unstructured":"Horak, D., Dostal, Z., Hapla, V., Kruzik, J., Sojka, R., Cermak, M.: Projector-less TFETI for contact problems: preliminary results. In: Civil-Comp Proceedings, vol. 111 (2017)"},{"key":"9_CR13","doi-asserted-by":"crossref","unstructured":"Ma, J., Saul, L., Savage, S., Voelker, G.: Identifying suspicious URLs: an application of large-scale online learning, pp. 681\u2013688 (2009). Cited By 173","DOI":"10.1145\/1553374.1553462"},{"key":"9_CR14","unstructured":"Munson, T., Sarich, J., Wild, S., Benson, S., McInnes, L.C.: TAO users manual. Technical report ANL\/MCS-TM-322. Argonne National Laboratory (2015). http:\/\/tinyurl.com\/tao-man"},{"key":"9_CR15","volume-title":"Algorithms and Architectures for Machine Learning Based on Regularized Neural Networks and Support Vector Approaches (Berichte Aus Der Informatik)","author":"M Rychetsky","year":"2001","unstructured":"Rychetsky, M.: Algorithms and Architectures for Machine Learning Based on Regularized Neural Networks and Support Vector Approaches (Berichte Aus Der Informatik). Shaker Verlag GmbH, Herzogenrath (2001)"},{"issue":"3","key":"9_CR16","doi-asserted-by":"publisher","first-page":"1064","DOI":"10.1109\/TIA.2012.2190816","volume":"48","author":"J Shi","year":"2012","unstructured":"Shi, J., Lee, W.J., Liu, Y., Yang, Y., Wang, P.: Forecasting power output of photovoltaic systems based on weather classification and support vector machines. IEEE Trans. Ind. Appl. 48(3), 1064\u20131069 (2012)","journal-title":"IEEE Trans. Ind. Appl."},{"key":"9_CR17","unstructured":"Smith, B.F., et al.: PETSc users manual. Technical report ANL-95\/11 - Revision 3.5. Argonne National Laboratory (2016). http:\/\/tinyurl.com\/petsc-man"},{"key":"9_CR18","doi-asserted-by":"crossref","unstructured":"Vishnu, A., Narasimhan, J., Holder, L., Kerbyson, D., Hoisie, A.: Fast and accurate support vector machines on large scale systems. In: 2015 IEEE International Conference on Cluster Computing, pp. 110\u2013119, September 2015","DOI":"10.1109\/CLUSTER.2015.26"}],"container-title":["Lecture Notes in Computer Science","High Performance Computing in Science and Engineering"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-97136-0_9","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,10,20]],"date-time":"2019-10-20T17:50:38Z","timestamp":1571593838000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-97136-0_9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783319971353","9783319971360"],"references-count":18,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-97136-0_9","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2018]]}}}