Ou, GeWang, YanHuang, LanPang, WeiCoghill, George MacLeodPhung, DinhTseng, Vincent S.Webb, Prof. Geoffrey I.Ho, BaoGanji, MohadesehRashidi, Lida2019-07-212019-07-212018-07-22Ou, G, Wang, Y, Huang, L, Pang, W & Coghill, G M 2018, ε-Distance Weighted Support Vector Regression. in D Phung, V S Tseng, P G I Webb, B Ho, M Ganji & L Rashidi (eds), Advances in Knowledge Discovery and Data Mining : 22nd Pacific-Asia Conference, PAKDD 2018, Melbourne, VIC, Australia, June 3-6, 2018, Proceedings, Part I., 17, Lecture Notes in Artificial Intelligence, Springer International Publishing, PAKDD 2018, Melbourne, Australia, 3/06/18. https://doi.org/10.1007/978-3-319-93034-3_17conference978331993033697833199303430302-9743ORCID: /0000-0002-1761-6659/work/52133917ORCID: /0000-0002-1761-6659/work/59923270ORCID: /0000-0002-2047-8277/work/63561533http://hdl.handle.net/2164/12610We gratefully thank Dr Teng Zhang and Prof Zhi-Hua Zhou for providing the source code of “LDM”, and their kind technical assistance. We also thank Prof Chih-Jen Lins team for providing the LIBSVM and LIBLINEAR packages and their support. This work is supported by the National Natural Science Foundation of China (Grant Nos.61472159, 61572227) and Development Project of Jilin Province of China (Grant Nos. 20140101180JC, 20160204022GX, 20180414012G H). This work is also partially supported by the 2015 Scottish Crucible Award funded by the Royal Society of Edinburgh and the 2016 PECE bursary provided by the Scottish Informatics & Computer Science Alliance (SICSA).571490engregression analysisSupport Vector RegressionDistance Weighted Support Vector RegressionDual Coordinate DescentAveraged Stochastic Gradient DescentQA75 Electronic computers. Computer scienceQA75Conference item10.1007/978-3-319-93034-3_17