A fast trust-region Newton method for softmax logistic regression Zaidi, Nayyar A. and Webb, Geoffrey I. 2017, A fast trust-region Newton method for softmax logistic regression, in SDM 2017 : Proceedings of the 2017 SIAM International Conference on Data Mining, SIAM, Philadelphia, Pa., pp. 705-713, doi: 10.1137/1.9781611974973.79. Attached Files Name Description MIMEType Size Downloads Title A fast trust-region Newton method for softmax logistic regression Author(s) Zaidi, Nayyar A. orcid.org/0000-0003-4024-2517 Webb, Geoffrey I. Conference name SIAM International Conference on Data Mining (2017 : Houston, Texas) Conference location Houston, Texas Conference dates 27-29 Apr. 2017 Title of proceedings SDM 2017 : Proceedings of the 2017 SIAM International Conference on Data Mining Editor(s) Chawla, Nitesh Wang, Wei Publication date 2017 Start page 705 End page 713 Total pages 9 Publisher SIAM Place of publication Philadelphia, Pa. ISBN 9781611974973 1611974976 Language eng DOI 10.1137/1.9781611974973.79 Indigenous content off HERDC Research category E1.1 Full written paper - refereed Free to Read? Yes Persistent URL http://hdl.handle.net/10536/DRO/DU:30135393 Document type: Conference Paper Collections: Faculty of Science, Engineering and Built Environment School of Information Technology Open Access Collection Related Links Link Description Link to full-text (open access)   Connect to published version Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au. Versions Version Filter Type Tue, 03 Mar 2020, 13:05:09 EST Tue, 03 Mar 2020, 14:49:02 EST Wed, 04 Mar 2020, 04:01:41 EST Wed, 04 Mar 2020, 05:05:01 EST Mon, 16 Mar 2020, 09:11:11 EST Mon, 16 Mar 2020, 09:14:09 EST Mon, 30 Mar 2020, 12:35:37 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 0 times in Scopus Search Google Scholar Access Statistics: 39 Abstract Views, 0 File Downloads  -  Detailed Statistics Created: Tue, 03 Mar 2020, 14:49:02 EST

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