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pro vyhledávání: '"Ives, Zachary G"'
Query-driven machine learning models have emerged as a promising estimation technique for query selectivities. Yet, surprisingly little is known about the efficacy of these techniques from a theoretical perspective, as there exist substantial gaps be
Externí odkaz:
http://arxiv.org/abs/2409.07014
In recent years, \emph{learned cardinality estimation} has emerged as an alternative to traditional query optimization methods: by training machine learning models over observed query performance, learned cardinality estimation techniques can accurat
Externí odkaz:
http://arxiv.org/abs/2312.01025
This volume contains the papers presented at the Third Workshop on Software Foundations for Data Interoperability (SFDI2019+) held on October 28, 2019, in Fukuoka, co-located with the 11th Asia-Pasific Symposium on Internetware (Internetware 2019). O
Externí odkaz:
http://arxiv.org/abs/1911.05900
Akademický článek
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Akademický článek
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As declarative query processing techniques expand in scope --- to the Web, data streams, network routers, and cloud platforms --- there is an increasing need for adaptive query processing techniques that can re-plan in the presence of failures or una
Externí odkaz:
http://arxiv.org/abs/1409.6288
Autor:
Ives, Zachary G.
Publikováno v:
Connect to this title online; UW restricted.
Thesis (Ph. D.)--University of Washington, 2002.
Vita. Includes bibliographical references (p. 166-185).
Vita. Includes bibliographical references (p. 166-185).
Externí odkaz:
http://hdl.handle.net/1773/6864
Publikováno v:
Proceedings of the VLDB Endowment (PVLDB), Vol. 5, No. 11, pp. 1280-1291 (2012)
In today's Web and social network environments, query workloads include ad hoc and OLAP queries, as well as iterative algorithms that analyze data relationships (e.g., link analysis, clustering, learning). Modern DBMSs support ad hoc and OLAP queries
Externí odkaz:
http://arxiv.org/abs/1208.0089
Publikováno v:
In Neuron 2 November 2016 92(3):617-621
Autor:
Talukdar, Partha Pratim, Jacob, Marie, Mehmood, Muhammad Salman, Crammer, Koby, Ives, Zachary G., Pereira, Fernando, Guha, Sudipto
Publikováno v:
Proceedings of the VLDB Endowment; 20240101, Issue: Preprints p785-796, 12p