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pro vyhledávání: '"Amita Gajewar"'
Autor:
Amita Gajewar, Allison Koenecke
Publikováno v:
Mining Data for Financial Applications ISBN: 9783030377199
MIDAS@PKDD
MIDAS@PKDD
For any financial organization, computing accurate quarterly forecasts for various products is one of the most critical operations. As the granularity at which forecasts are needed increases, traditional statistical time series models may not scale w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fac8a4330a67305ceb2e151318960a50
https://doi.org/10.1007/978-3-030-37720-5_2
https://doi.org/10.1007/978-3-030-37720-5_2
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 32
Revenue forecasting is required by most enterprises for strategic business planning and for providing expected future results to investors. However, revenue forecasting processes in most companies are time-consuming and error-prone as they are perfor
Publikováno v:
IEEE BigData
In the world of display advertising, advertisers often book a campaign ahead of time and therefore reserve the corresponding supply-inventory. However, they can choose to cancel the campaign any time prior to the start date. When such cancellation ha
Publikováno v:
Journal of Graph Algorithms and Applications. 17:567-573
The celebrated Four-Color Theorem was rst conjectured in the 1850’s. Since then there had been many partial results. More than a century later, it was rst proved by Appel and Haken [1] and then subsequently improved by Robertson et al. [8]. These p
Autor:
Raymie Stata, Dongming Jiang, Sunil Nagaraj, Kevin J. Lang, Joaquin Delgado, Shirshanka Das, Arathi Seshan, Chavdar Botev, Amita Gajewar, Bhaskar Ghosh, Michael Bindeberger-Ortega, Swaroop Jagadish
Publikováno v:
WSDM
We introduce and formalize a novel constrained path optimization problem that is the heart of the real-time ad serving task in the Yahoo! (formerly RightMedia) Display Advertising Exchange. In the Exchange, the ad server's task for each display oppor
Autor:
Amita Gajewar, Atish Das Sarma
Publikováno v:
SDM
We consider the problem of identifying a team of skilled individuals for collaboration, in the presence of a social network. Each node in the social network may be an expert in one or more skills. Edge weights specify affinity or collaborative compat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::56d857158c1e0b2a83d913d802cfb8b7