Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Bojan Karlas"'
Autor:
Fotis Psallidas, Yiwen Zhu, Bojan Karlas, Jordan Henkel, Matteo Interlandi, Subru Krishnan, Brian Kroth, Venkatesh Emani, Wentao Wu, Ce Zhang, Markus Weimer, Avrilia Floratou, Carlo Curino, Konstantinos Karanasos
Publikováno v:
ACM SIGMOD Record. 51:30-37
The recent success of machine learning (ML) has led to an explosive growth of systems and applications built by an ever-growing community of system builders and data science (DS) practitioners. This quickly shifting panorama, however, is challenging
Publikováno v:
Proceedings of the VLDB Endowment. 11:2054-2057
We demonstrate ease.ml, a multi-tenant machine learning service we host at ETH Zurich for various research groups. Unlike existing machine learning services, ease.ml presents a novel architecture that supports multi-tenant, cost-aware model selection
Publikováno v:
Proceedings of the VLDB Endowment, 12 (12)
Developing machine learning (ML) applications is similar to developing traditional software-it is often an iterative process in which developers navigate within a rich space of requirements, design decisions, implementations, empirical quality, and p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a639b417a94638526a87bb906e4ef419
https://hdl.handle.net/20.500.11850/395903
https://hdl.handle.net/20.500.11850/395903