Prescriptive analytics through constrained bayesian optimization

Harikumar, Haripriya, Rana, Santu, Gupta, Sunil, Nguyen, Thin, Kaimal, Ramachandra and Venkatesh, Svetha 2018, Prescriptive analytics through constrained bayesian optimization, in PAKDD 2018 : Advances in Knowledge Discovery and Data Mining : Proceedings of 22nd Pacific-Asia Conference, Springer, Cham, Switzerland, pp. 335-347, doi: 10.1007/978-3-319-93034-3_27.

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Title Prescriptive analytics through constrained bayesian optimization
Author(s) Harikumar, Haripriya
Rana, SantuORCID iD for Rana, Santu orcid.org/0000-0003-2247-850X
Gupta, SunilORCID iD for Gupta, Sunil orcid.org/0000-0002-3308-1930
Nguyen, ThinORCID iD for Nguyen, Thin orcid.org/0000-0003-3467-8963
Kaimal, Ramachandra
Venkatesh, SvethaORCID iD for Venkatesh, Svetha orcid.org/0000-0001-8675-6631
Conference name Knowledge Discovery and Data Mining. Pacific-Asia Conference (22nd : 2018 : Melbourne, Victoria)
Conference location Melbourne, Victoria
Conference dates 2018/06/03 - 2018/06/06
Title of proceedings PAKDD 2018 : Advances in Knowledge Discovery and Data Mining : Proceedings of 22nd Pacific-Asia Conference
Editor(s) Phung, D
Tseng, V
Webb, G
Ho, B
Ganji, M
Rashidi, L
Publication date 2018
Series Lecture Notes in Computer Science
Start page 335
End page 347
Total pages 13
Publisher Springer
Place of publication Cham, Switzerland
Keyword(s) Prescriptive analytics
Bayesian optimization
Linear and nonlinear classifiers
Constrained optimization
Science & Technology
Technology
Computer Science, Artificial Intelligence
Computer Science, Information Systems
Computer Science, Theory & Methods
Computer Science
INVERSE CLASSIFICATION PROBLEM
ISBN 9783319930398
ISSN 0302-9743
1611-3349
Language eng
DOI 10.1007/978-3-319-93034-3_27
Field of Research 08 Information And Computing Sciences
HERDC Research category E1 Full written paper - refereed
ERA Research output type E Conference publication
Grant ID ARC FL170100006
Persistent URL http://hdl.handle.net/10536/DRO/DU:30110016

Document type: Conference Paper
Collection: School of Information Technology
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