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pro vyhledávání: '"Haas, Peter J"'
Stochastic SketchRefine: Scaling In-Database Decision-Making under Uncertainty to Millions of Tuples
Autor:
Haque, Riddho R., Mai, Anh L., Brucato, Matteo, Abouzied, Azza, Haas, Peter J., Meliou, Alexandra
Decision making under uncertainty often requires choosing packages, or bags of tuples, that collectively optimize expected outcomes while limiting risks. Processing Stochastic Package Queries (SPQs) involves solving very large optimization problems o
Externí odkaz:
http://arxiv.org/abs/2411.17915
Autor:
Mai, Anh L., Wang, Pengyu, Abouzied, Azza, Brucato, Matteo, Haas, Peter J., Meliou, Alexandra
A package query returns a package - a multiset of tuples - that maximizes or minimizes a linear objective function subject to linear constraints, thereby enabling in-database decision support. Prior work has established the equivalence of package que
Externí odkaz:
http://arxiv.org/abs/2307.02860
What-if analysis (WIA), crucial for making data-driven decisions, enables users to understand how changes in variables impact outcomes and explore alternative scenarios. However, existing WIA research focuses on supporting the workflows of data scien
Externí odkaz:
http://arxiv.org/abs/2212.13643
Random sampling has become a crucial component of modern data management systems. Although the literature on database sampling is large, there has been relatively little work on the problem of maintaining a sample in the presence of arbitrary inserti
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A80839
https://tud.qucosa.de/api/qucosa%3A80839/attachment/ATT-0/
https://tud.qucosa.de/api/qucosa%3A80839/attachment/ATT-0/
Perhaps the most flexible synopsis of a database is a random sample of the data; such samples are widely used to speed up processing of analytic queries and data-mining tasks, enhance query optimization, and facilitate information integration. In thi
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A79145
https://tud.qucosa.de/api/qucosa%3A79145/attachment/ATT-0/
https://tud.qucosa.de/api/qucosa%3A79145/attachment/ATT-0/
A variety of schemes have been proposed in the literature to speed up query processing and analytics by incrementally maintaining a bounded-size uniform sample from a dataset in the presence of a sequence of insertion, deletion, and update transactio
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A83116
https://tud.qucosa.de/api/qucosa%3A83116/attachment/ATT-0/
https://tud.qucosa.de/api/qucosa%3A83116/attachment/ATT-0/
Perhaps the most flexible synopsis of a database is a uniform random sample of the data; such samples are widely used to speed up processing of analytic queries and data-mining tasks, enhance query optimization, and facilitate information integration
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A82220
https://tud.qucosa.de/api/qucosa%3A82220/attachment/ATT-0/
https://tud.qucosa.de/api/qucosa%3A82220/attachment/ATT-0/
The fundamental goal of business data analysis is to improve business decisions using data. Business users often make decisions to achieve key performance indicators (KPIs) such as increasing customer retention or sales, or decreasing costs. To disco
Externí odkaz:
http://arxiv.org/abs/2109.06160
Probability proportional to size (PPS) sampling schemes with a target sample size aim to produce a sample comprising a specified number $n$ of items while ensuring that each item in the population appears in the sample with a probability proportional
Externí odkaz:
http://arxiv.org/abs/2105.10809