Zobrazeno 1 - 10
of 11
pro vyhledávání: '"Erika Duriakova"'
Publikováno v:
2021 IEEE International Conference on Big Data (Big Data).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3150ac680ae8916c284977ecb7926e3a
https://doi.org/10.1109/bigdata52589.2021.9671975
https://doi.org/10.1109/bigdata52589.2021.9671975
Autor:
Weipeng Huang, James R. Geraci, Neil Hurley, Elias Z. Tragos, Erika Duriakova, Aonghus Lawlor, Barry Smyth
Publikováno v:
Machine Learning and Knowledge Discovery in Databases ISBN: 9783030676605
ECML/PKDD (2)
ECML/PKDD (2)
We propose a framework for fully decentralised machine learning and apply it to latent factor models for top-N recommendation. The training data in a decentralised learning setting is distributed across multiple agents, who jointly optimise a common
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::48ca1351e4543c6df993a4339a983d22
https://doi.org/10.1007/978-3-030-67661-2_19
https://doi.org/10.1007/978-3-030-67661-2_19
Autor:
Erika Duriakova, Francisco J. Peña, Elias Z. Tragos, Diarmuid O'Reilly-Morgan, Neil Hurley, Barry Smyth, Aonghus Lawlor
Publikováno v:
RecSys
Nowadays we commonly have multiple sources of data associated with items. Users may provide numerical ratings, or implicit interactions, but may also provide textual reviews. Although many algorithms have been proposed to jointly learn a model over b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d01e14841d5655ea8a4deb3a2487488e
https://doi.org/10.1145/3383313.3412207
https://doi.org/10.1145/3383313.3412207
Publikováno v:
IEEE BigData
Computation of the single-source shortest path (SSSP) is a fundamental primitive in many network analytics tasks. With the increasing size of networks to be analysed, there is a need for efficient tools to compute shortest paths, especially on the wi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a02251f33eae5af0d6453f1b855d7832
https://doi.org/10.1109/bigdata47090.2019.9006237
https://doi.org/10.1109/bigdata47090.2019.9006237
Autor:
Panagiotis Symeonidis, Erika Duriakova, Aonghus Lawlor, Elias Z. Tragos, Barry Smyth, Francisco J. Peña, Neil Hurley, James R. Geraci
Publikováno v:
RecSys
Conventional approaches to matrix factorisation (MF) typically rely on a centralised collection of user data for building a MF model. This approach introduces an increased risk when it comes to user privacy. In this short paper we propose an alternat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1c1853cb15a7d4c79cfc323e14bdd391
https://doi.org/10.1145/3298689.3347035
https://doi.org/10.1145/3298689.3347035
Publikováno v:
ICPP
We consider the loop less k-shortest path (KSP) problem. Although this problem has been studied in the sequential setting for at least the last two decades, no good parallel implementations are known. In this paper, we provide (i) a first systematic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d6d278ca701021a319667c0cd9c74814
https://doi.org/10.1145/3225058.3225075
https://doi.org/10.1145/3225058.3225075
Autor:
Samuel Williams, Erika Duriakova, Aydin Buluc, Leonid Oliker, Armando Fox, John R. Gilbert, Shoaib Kamil, Adam Lugowski
Publikováno v:
Lugowski, A; Kamil, S; Buluç, A; Williams, S; Duriakova, E; Oliker, L; et al.(2015). Parallel processing of filtered queries in attributed semantic graphs. Journal of Parallel and Distributed Computing, 79-80, 115-131. doi: 10.1016/j.jpdc.2014.08.010. UC Berkeley: Retrieved from: http://www.escholarship.org/uc/item/91f283qf
Execution of complex analytic queries on massive semantic graphs is a challenging problem in big-data analytics that requires high-performance parallel computing. In a semantic graph, vertices and edges carry attributes of various types and the analy
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9aaaa62c5e4ec8c4896ac107b9cf8b9d
https://doi.org/10.1016/j.jpdc.2014.08.010
https://doi.org/10.1016/j.jpdc.2014.08.010
Autor:
Neil Hurley, Erika Duriakova
Publikováno v:
2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4a3a71f70a3bd2992ba3294ae73b627c
https://doi.org/10.1109/asonam.2016.7752252
https://doi.org/10.1109/asonam.2016.7752252
Autor:
Erika Duriakova, Neil Hurley
Publikováno v:
ASONAM
Among the many community-finding algorithms that have been proposed in the last decade and more, the Infomap algorithm of Rosvall and Bergstrom has proven among the best. The algorithm finds good community structure in directed as well as undirected
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::009869e40a7939fe419fb8bd47228786
https://doi.org/10.1145/2808797.2809356
https://doi.org/10.1145/2808797.2809356
Publikováno v:
COSN
Community-finding in graphs is the process of identifying highly cohesive vertex subsets. Recently the vertex-centric approach has been found effective for scalable graph processing and is implemented in systems such as GraphLab and Pregel. In the ve
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e28235bedc4c4599f2d29271ebd4805c
https://doi.org/10.1145/2660460.2660474
https://doi.org/10.1145/2660460.2660474