Zobrazeno 1 - 10
of 40
pro vyhledávání: '"Borkar, Vinayak"'
Autor:
Carman Jr., E. Preston, Westmann, Till, Borkar, Vinayak R., Carey, Michael J., Tsotras, Vassilis J.
The wide use of XML for document management and data exchange has created the need to query large repositories of XML data. To efficiently query such large data collections and take advantage of parallelism, we have implemented Apache VXQuery, an ope
Externí odkaz:
http://arxiv.org/abs/1504.00331
Autor:
Kim, Taewoo, Li, Wenhai, Behm, Alexander, Cetindil, Inci, Vernica, Rares, Borkar, Vinayak, Carey, Michael J., Li, Chen
Publikováno v:
In Information Systems February 2020 88
Autor:
Alsubaiee, Sattam, Altowim, Yasser, Altwaijry, Hotham, Behm, Alexander, Borkar, Vinayak, Bu, Yingyi, Carey, Michael, Cetindil, Inci, Cheelangi, Madhusudan, Faraaz, Khurram, Gabrielova, Eugenia, Grover, Raman, Heilbron, Zachary, Kim, Young-Seok, Li, Chen, Li, Guangqiang, Ok, Ji Mahn, Onose, Nicola, Pirzadeh, Pouria, Tsotras, Vassilis, Vernica, Rares, Wen, Jian, Westmann, Till
AsterixDB is a new, full-function BDMS (Big Data Management System) with a feature set that distinguishes it from other platforms in today's open source Big Data ecosystem. Its features make it well-suited to applications like web data warehousing, s
Externí odkaz:
http://arxiv.org/abs/1407.0454
There is a growing need for distributed graph processing systems that are capable of gracefully scaling to very large graph datasets. Unfortunately, this challenge has not been easily met due to the intense memory pressure imposed by process-centric,
Externí odkaz:
http://arxiv.org/abs/1407.0455
Aggregation has been an important operation since the early days of relational databases. Today's Big Data applications bring further challenges when processing aggregation queries, demanding adaptive aggregation algorithms that can process large vol
Externí odkaz:
http://arxiv.org/abs/1311.0059
Autor:
Rosen, Joshua, Polyzotis, Neoklis, Borkar, Vinayak, Bu, Yingyi, Carey, Michael J., Weimer, Markus, Condie, Tyson, Ramakrishnan, Raghu
Large datasets ("Big Data") are becoming ubiquitous because the potential value in deriving insights from data, across a wide range of business and scientific applications, is increasingly recognized. In particular, machine learning - one of the foun
Externí odkaz:
http://arxiv.org/abs/1303.3517
Autor:
Bu, Yingyi, Borkar, Vinayak, Carey, Michael J., Rosen, Joshua, Polyzotis, Neoklis, Condie, Tyson, Weimer, Markus, Ramakrishnan, Raghu
In this paper, we present the case for a declarative foundation for data-intensive machine learning systems. Instead of creating a new system for each specific flavor of machine learning task, or hardcoding new optimizations, we argue for the use of
Externí odkaz:
http://arxiv.org/abs/1203.0160
Akademický článek
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Autor:
Papakonstantinou, Yannis, Borkar, Vinayak, Orgiyan, Maxim, Stathatos, Kostas, Suta, Lucian, Vassalos, Vasilis, Velikhov, Pavel
Publikováno v:
In Data & Knowledge Engineering 2003 44(3):299-322
Autor:
Carman, E. Preston, Westmann, Till, Borkar, Vinayak R., Carey, Michael J., Tsotras, Vassilis J.
The wide use of XML for document management and data exchange has created the need to query large repositories of XML data. To efficiently query such large data collections and take advantage of parallelism, we have implemented Apache VXQuery, an ope
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::87ece20177a54185aee98ac3e4d38594
http://arxiv.org/abs/1504.00331
http://arxiv.org/abs/1504.00331