Zobrazeno 1 - 10
of 52
pro vyhledávání: '"Zoi Kaoudi"'
Autor:
Stefano Giovanni Rizzo, Yixian Chen, Linsey Pang, Ji Lucas, Zoi Kaoudi, Jorge Quiane, Sanjay Chawla
Publikováno v:
Knowledge and Information Systems. 64:2515-2541
Publikováno v:
Proceedings of the VLDB Endowment. 15:3714-3717
Existing automated machine learning solutions and intelligent discovery assistants are popular tools that facilitate the end-user with the design of data science (DS) pipelines. However, they yield limited applicability for a wide range of real-world
Publikováno v:
Proceedings of the VLDB Endowment. 14:2707-2710
Parameter servers (PSs) ease the implementation of distributed machine learning systems, but their performance can fall behind that of single machine baselines due to communication overhead. We demonstrate Lapse, an open source PS with dynamic parame
Publikováno v:
Proceedings of the 2022 International Conference on Management of Data.
Publikováno v:
2022 IEEE 38th International Conference on Data Engineering (ICDE).
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:
Proceedings of the VLDB Endowment. 13:2889-2892
Knowledge graphs represented as RDF datasets are integral to many machine learning applications. RDF is supported by a rich ecosystem of data management systems and tools, most notably RDF database systems that provide a SPARQL query interface. Surpr
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:
Synthesis Lectures on Data Management. 15:1-103
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