File Download

There are no files associated with this item.

Supplementary

Conference Paper: Learning Resource Allocation and Pricing for Cloud Profit Maximization

TitleLearning Resource Allocation and Pricing for Cloud Profit Maximization
Authors
Issue Date2019
Citation
The Thirty-Third Association for the Advancement of Artificial Intelligence (AAAI) Conference on Artificial Intelligence (AAAI-19), Honolulu, Hawaii, USA, 27 January– 1 February 2019 How to Cite?
DescriptionTech Session 9: Planning, Routing, and Scheduling 2 - Oral Presentation no. 3542
Persistent Identifierhttp://hdl.handle.net/10722/273018

 

DC FieldValueLanguage
dc.contributor.authorDu, B-
dc.contributor.authorWu, C-
dc.contributor.authorHuang, Z-
dc.date.accessioned2019-08-06T09:20:59Z-
dc.date.available2019-08-06T09:20:59Z-
dc.date.issued2019-
dc.identifier.citationThe Thirty-Third Association for the Advancement of Artificial Intelligence (AAAI) Conference on Artificial Intelligence (AAAI-19), Honolulu, Hawaii, USA, 27 January– 1 February 2019-
dc.identifier.urihttp://hdl.handle.net/10722/273018-
dc.descriptionTech Session 9: Planning, Routing, and Scheduling 2 - Oral Presentation no. 3542-
dc.languageeng-
dc.relation.ispartofThe Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19)-
dc.titleLearning Resource Allocation and Pricing for Cloud Profit Maximization-
dc.typeConference_Paper-
dc.identifier.emailWu, C: cwu@cs.hku.hk-
dc.identifier.emailHuang, Z: zhiyi@cs.hku.hk-
dc.identifier.authorityWu, C=rp01397-
dc.identifier.authorityHuang, Z=rp01804-
dc.identifier.hkuros299710-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats