Zobrazeno 1 - 10
of 59
pro vyhledávání: '"Jorge-Arnulfo Quiané-Ruiz"'
Wayang AgoraEO Plugin: The Framework for Scalable EO Workflows Currently, Earth Observation (EO) platforms provide datasets, algorithms, and processing capabilities. Nevertheless, each platform proposes its own exclusive habitat to discover, process,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ad625936e56c6177a66a2740ae197472
https://doi.org/10.5194/egusphere-egu23-17046
https://doi.org/10.5194/egusphere-egu23-17046
Autor:
Gábor E. Gévay, Tilmann Rabl, Sebastian Breß, Loránd Madai-Tahy, Jorge-Arnulfo Quiané-Ruiz, Volker Markl
Publikováno v:
ACM SIGMOD Record. 51:60-67
Modern data analysis tasks often involve control flow statements, such as the iterations in PageRank and K-means. To achieve scalability, developers usually implement these tasks in distributed dataflow systems, such as Spark and Flink. Designers of
Publikováno v:
World Wide Web. 25:971-1003
Implementing complex algorithms for big data, artificial intelligence, and graph processing requires enormous effort. Succinct, declarative programs to solve complex problems that can be efficiently executed for batching and streaming data are in dem
Publikováno v:
Proceedings of the VLDB Endowment. 15:659-672
Protection of personal data has been raised to be among the top requirements of modern systems. At the same time, it is now frequent that the owner of the data and the owner of the computing infrastructure are two entities with limited trust between
Publikováno v:
Proceedings of the VLDB Endowment. 14:2843-2846
In this paper we present our work on compliant geo-distributed data processing. Our work focuses on the new dimension of dataflow constraints that regulate the movement of data across geographical or institutional borders. For example, European direc
Publikováno v:
ACM SIGMOD Record. 49:6-11
Data science and artificial intelligence are driven by a plethora of diverse data-related assets, including datasets, data streams, algorithms, processing software, compute resources, and domain knowledge. As providing all these assets requires a hug
Publikováno v:
Jorge Arnulfo Quiané Ruiz
Graphs in many applications, such as social networks and IoT, are inherently streaming, involving continuous additions and deletions of vertices and edges at high rates. Constructing random walks in a graph, i.e., sequences of vertices selected with
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::578e450c49a117c5817dc2cd589a7e36
Publikováno v:
Jorge Arnulfo Quiané Ruiz
A core operation in data discovery is to find joinable tables for a given table. Real-world tables include both unary and n-ary join keys. However, existing table discovery systems are optimized for unary joins and are ineffective and slow in the exi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d049a022000af8ab319b35cc17828e9d
http://arxiv.org/abs/2110.00318
http://arxiv.org/abs/2110.00318
Publikováno v:
SIGMOD Conference
Machine Learning (ML) is quickly becoming a prominent method in many data management components, including query optimizers which have recently shown very promising results. However, the low availability of training data (i.e., large query workloads
Publikováno v:
SIGMOD Conference
Many common data analysis tasks, such as performing hyperparameter optimization, processing a partitioned graph, and treating a matrix as a vector of vectors, offer natural opportunities for nested-parallel operations, i.e., launching parallel operat