Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Kevin Innerebner"'
Autor:
Sebastian Baunsgaard, Matthias Boehm, Kevin Innerebner, Mito Kehayov, Florian Lackner, Olga Ovcharenko, Arnab Phani, Tobias Rieger, David Weissteiner, Sebastian Benjamin Wrede
Publikováno v:
Proceedings of the 31st ACM International Conference on Information & Knowledge Management.
Autor:
Patrick Damme, Marius Birkenbach, Constantinos Bitsakos, Matthias Boehm, Philippe Bonnet, Florina Ciorba, Mark Dokter, Pawel Dowgiallo, Ahmed Eleliemy, Christian Faerber, Georgios Goumas, Dirk Habich, Niclas Hedam, Marlies Hofer, Wenjun Huang, Kevin Innerebner, Vasileios Karakostas, Roman Kern, Tomaž Kosar, Daniel Krems, Andreas Laber, Wolfgang Lehner, Eric Mier, Marcus Paradies, Bernhard Peischl, Gabrielle Poerwawinata, Stratos Psomadakis, Tilmann Rabl, Piotr Ratuszniak, Pedro Silva, Nikolai Skuppin, Andreas Starzacher, Benjamin Steinwender, Ilin Tolovski, Pınar Tözün, Wojciech Ulatowski, Yuanyuan Wang, Izajasz Wrosz, Aleš Zamuda, Ce Zhang, Xiao Xiang Zhu, Alexander Krause
Publikováno v:
Damme, P, Birkenbach, M, Bitsakos, C, Boehm, M, Bonnet, P, Ciorba, F, Dokter, M, Dowgiallo, P, Eleliemy, A, Faerber, C, Goumas, G, Habich, D, Hedam, N, Hofer, M, Huang, W, Innerebner, K, Karakostas, V, Kern, R, Kosar, T, Krause, A, Krems, D, Laber, A, Lehner, W, Mier, E, Paradies, M, Peischl, B, Poerwawinata, G, Psomadakis, S, Rabl, T, Ratuszniak, P, Silva, P, Skuppin, N, Starzacher, A, Steinwender, B, Tolovski, I, Tözün, P, Ulatowski, W, Wang, Y, Wrosz, I, Zamuda, A, Zhang, C & Zhu, X X 2022, DAPHNE: An Open and Extensible System Infrastructure for Integrated Data Analysis Pipelines . in Conference on Innovative Data Systems Research . Santa Cruz, California, USA . < http://cidrdb.org/cidr2022/papers/p4-damme.pdf >
Benjamin Steinwender
Benjamin Steinwender
Integrated data analysis (IDA) pipelines---that combine data management (DM) and query processing, high-performance computing (HPC), and machine learning (ML) training and scoring---become increasingly common in practice. Interestingly, systems of th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::ef97c54fb73d8eceb46f77197e7fe80d
https://pure.itu.dk/ws/files/86467917/CIDR2022.pdf
https://pure.itu.dk/ws/files/86467917/CIDR2022.pdf
Autor:
Kevin Innerebner, Michael Hildebrand, Alireza Rezaei Mahdiraji, Claus Neubauer, Sebastian Benjamin Wrede, Steffen Zeuch, Ankit Chaudhary, Sergey Redyuk, Philipp M. Grulich, Behrouz Derakhshan, Tobias Rieger, Sarah Osterburg, Olga Ovcharenko, Sebastian Baunsgaard, Stefan Geißelsöder, Volker Markl, Matthias Boehm
Publikováno v:
SIGMOD Conference
Data science workflows are largely exploratory, dealing with under-specified objectives, open-ended problems, and unknown business value. Therefore, little investment is made in systematic acquisition, integration, and pre-processing of data. This la