Zobrazeno 1 - 10
of 333
pro vyhledávání: '"Sakr, Sherif A."'
With the booming demand for machine learning applications, it has been recognized that the number of knowledgeable data scientists can not scale with the growing data volumes and application needs in our digital world. In response to this demand, sev
Externí odkaz:
http://arxiv.org/abs/2204.08358
Publikováno v:
In Future Generation Computer Systems February 2025 163
Novel technologies in automated machine learning ease the complexity of algorithm selection and hyperparameter optimization. Hyperparameters are important for machine learning models as they significantly influence the performance of machine learning
Externí odkaz:
http://arxiv.org/abs/2108.13066
Publikováno v:
In Expert Systems With Applications 1 June 2024 243
Autor:
Sakr, Sherif, Bonifati, Angela, Voigt, Hannes, Iosup, Alexandru, Ammar, Khaled, Angles, Renzo, Aref, Walid, Arenas, Marcelo, Besta, Maciej, Boncz, Peter A., Daudjee, Khuzaima, Della Valle, Emanuele, Dumbrava, Stefania, Hartig, Olaf, Haslhofer, Bernhard, Hegeman, Tim, Hidders, Jan, Hose, Katja, Iamnitchi, Adriana, Kalavri, Vasiliki, Kapp, Hugo, Martens, Wim, Özsu, M. Tamer, Peukert, Eric, Plantikow, Stefan, Ragab, Mohamed, Ripeanu, Matei R., Salihoglu, Semih, Schulz, Christian, Selmer, Petra, Sequeda, Juan F., Shinavier, Joshua, Szárnyas, Gábor, Tommasini, Riccardo, Tumeo, Antonino, Uta, Alexandru, Varbanescu, Ana Lucia, Wu, Hsiang-Yun, Yakovets, Nikolay, Yan, Da, Yoneki, Eiko
Graphs are by nature unifying abstractions that can leverage interconnectedness to represent, explore, predict, and explain real- and digital-world phenomena. Although real users and consumers of graph instances and graph workloads understand these a
Externí odkaz:
http://arxiv.org/abs/2012.06171
The abundance of interconnected data has fueled the design and implementation of graph generators reproducing real-world linking properties, or gauging the effectiveness of graph algorithms, techniques and applications manipulating these data. We con
Externí odkaz:
http://arxiv.org/abs/2001.07906
With the continuous and vast increase in the amount of data in our digital world, it has been acknowledged that the number of knowledgeable data scientists can not scale to address these challenges. Thus, there was a crucial need for automating the p
Externí odkaz:
http://arxiv.org/abs/1906.02287
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Autor:
Elshawi, Radwa, Sakr, Sherif
Recently, we have been witnessing huge advancements in the scale of data we routinely generate and collect in pretty much everything we do, as well as our ability to exploit modern technologies to process, analyze and understand this data. The inters
Externí odkaz:
http://arxiv.org/abs/1709.07493
Eliminating duplicate data in primary storage of clouds increases the cost-efficiency of cloud service providers as well as reduces the cost of users for using cloud services. Existing primary deduplication techniques either use inline caching to exp
Externí odkaz:
http://arxiv.org/abs/1702.08153