Sparse approximation for Gaussian process with derivative observations Yang, Ang, Li, Cheng, Rana, Santu, Gupta, Sunil and Venkatesh, Svetha 2018, Sparse approximation for Gaussian process with derivative observations, in AI 2018: Proceedings of the 31st Australasian Joint Conference on Artificial Intelligence, Springer, Cham, Switzerland, pp. 507-518, doi: 10.1007/978-3-030-03991-2_46. Attached Files Name Description MIMEType Size Downloads Title Sparse approximation for Gaussian process with derivative observations Author(s) Yang, Ang Li, Cheng Rana, Santu orcid.org/0000-0003-2247-850X Gupta, Sunil orcid.org/0000-0002-3308-1930 Venkatesh, Svetha orcid.org/0000-0001-8675-6631 Conference name Australian Computer Society. Conference (31st : 2018 : Wellington, N.Z.) Conference location Wellington, N.Z. Conference dates 2018/12/11 - 2018/12/14 Title of proceedings AI 2018: Proceedings of the 31st Australasian Joint Conference on Artificial Intelligence Editor(s) Mitrovic, Tanja Xue, Bing Li, Xiaodong Publication date 2018 Series Australian Computer Society Conference Start page 507 End page 518 Total pages 12 Publisher Springer Place of publication Cham, Switzerland Keyword(s) Sparse Gaussian process model Bayesian optimisation Derivative-based ISBN 9783030039905 ISSN 0302-9743 1611-3349 Language eng DOI 10.1007/978-3-030-03991-2_46 Field of Research 08 Information and Computing Sciences HERDC Research category E1 Full written paper - refereed Grant ID ARC Laureate FL170100006 Copyright notice ©2018, Springer Nature Switzerland AG Persistent URL http://hdl.handle.net/10536/DRO/DU:30116363 Document type: Conference Paper Collections: Faculty of Science, Engineering and Built Environment Centre for Pattern Recognition and Data Analytics (PRADA) Related Links Link Description 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. Versions Version Filter Type Thu, 03 Jan 2019, 13:55:27 EST Thu, 03 Jan 2019, 13:55:58 EST Fri, 04 Jan 2019, 04:00:53 EST Wed, 16 Jan 2019, 14:34:51 EST Fri, 01 Mar 2019, 13:58:08 EST Thu, 04 Apr 2019, 13:27:19 EST Fri, 05 Apr 2019, 05:02:59 EST Wed, 10 Apr 2019, 10:32:41 EST Wed, 10 Apr 2019, 10:35:59 EST Wed, 10 Apr 2019, 10:36:51 EST Sat, 09 Jan 2021, 01:32:42 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 0 times in Scopus Search Google Scholar Access Statistics: 246 Abstract Views, 0 File Downloads  -  Detailed Statistics Created: Thu, 04 Apr 2019, 13:27:19 EST

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