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pro vyhledávání: '"Sheoran, Nikhil"'
Autor:
Sheoran, Nikhil, Chockchowwat, Supawit, Chheda, Arav, Wang, Suwen, Verma, Riya, Park, Yongjoo
For exploratory data analysis, it is often desirable to know what answers you are likely to get before actually obtaining those answers. This can potentially be achieved by designing systems to offer the estimates of a data operation result -- say op
Externí odkaz:
http://arxiv.org/abs/2303.04103
Autor:
Sheoran, Nikhil, Mitra, Subrata, Porwal, Vibhor, Ghetia, Siddharth, Varshney, Jatin, Mai, Tung, Rao, Anup, Maddukuri, Vikas
The goal of Approximate Query Processing (AQP) is to provide very fast but "accurate enough" results for costly aggregate queries thereby improving user experience in interactive exploration of large datasets. Recently proposed Machine-Learning based
Externí odkaz:
http://arxiv.org/abs/2201.12420
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence, vol. 33, July 2019, pp. 257-64
The 'old world' instrument, survey, remains a tool of choice for firms to obtain ratings of satisfaction and experience that customers realize while interacting online with firms. While avenues for survey have evolved from emails and links to pop-ups
Externí odkaz:
http://arxiv.org/abs/2006.06323
Autor:
Mitra, Subrata, Mondal, Shanka Subhra, Sheoran, Nikhil, Dhake, Neeraj, Nehra, Ravinder, Simha, Ramanuja
Large multi-tenant production clusters often have to handle a variety of jobs and applications with a variety of complex resource usage characteristics. It is non-trivial and non-optimal to manually create placement rules for scheduling that would de
Externí odkaz:
http://arxiv.org/abs/1907.12916