Zobrazeno 1 - 10
of 75
pro vyhledávání: '"Benjamin I P Rubinstein"'
Publikováno v:
Transactions of the Association for Computational Linguistics, Vol 12 (2024)
Externí odkaz:
https://doaj.org/article/62e112d7ae124329b74f0157ece9530a
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering. :1-18
Automating physical database design has remained a long-term interest in database research due to substantial performance gains afforded by optimised structures. Despite significant progress, a majority of today's commercial solutions are highly manu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::544a99f2ae17158117a1757dc80950d6
https://doi.org/10.1109/tkde.2023.3271664
https://doi.org/10.1109/tkde.2023.3271664
Publikováno v:
Proceedings of the VLDB Endowment. 16:216-229
Effective physical database design tuning requires selection of several physical design structures (PDS), such as indices and materialised views, whose combination influences overall system performance in a non-linear manner. While the simplicity of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0d5253071359039d2a83896b36bf50a1
https://doi.org/10.14778/3565816.3565824
https://doi.org/10.14778/3565816.3565824
Autor:
Andrew C. Cullen, Benjamin I. P. Rubinstein, Sithamparanathan Kandeepan, Barry Flower, Philip H. W. Leong
Publikováno v:
Artificial Intelligence Review.
The advent of the Internet of Things and 5G has further accelerated the growth in devices attempting to gain access to the wireless spectrum. A consequence of this has been the commensurate growth in spectrum conflict and congestion across the wirele
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0dbda2a9008f35a93069bf773f1bf297
https://doi.org/10.1007/s10462-023-10449-9
https://doi.org/10.1007/s10462-023-10449-9
Publikováno v:
IEEE Transactions on Information Theory. 68:538-548
Blowfish privacy is a recent generalisation of differential privacy that enables improved utility while maintaining privacy policies with semantic guarantees, a factor that has driven the popularity of differential privacy in computer science. This p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4d901312acfc19e17679fea4bef0e87a
https://doi.org/10.1109/tit.2021.3120371
https://doi.org/10.1109/tit.2021.3120371
Entity resolution (record linkage or deduplication) is the process of identifying and linking duplicate records in databases. In this paper, we propose a Bayesian graphical approach for entity resolution that links records to latent entities, where t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c1a92479cf42f6c552953efe9062a506
Publikováno v:
Machine Learning and Knowledge Discovery in Databases ISBN: 9783031264085
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::33da523103f80261cc3f24152390ed87
https://doi.org/10.1007/978-3-031-26409-2_17
https://doi.org/10.1007/978-3-031-26409-2_17
Autor:
Sandamal Weerasinghe, Tamas Abraham, Tansu Alpcan, Sarah M. Erfani, Christopher Leckie, Benjamin I. P. Rubinstein
Publikováno v:
2022 IEEE 61st Conference on Decision and Control (CDC).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4575d12d8b1e9f5bd5df387eaf1b3fe5
https://doi.org/10.1109/cdc51059.2022.9992383
https://doi.org/10.1109/cdc51059.2022.9992383
Publikováno v:
2022 IEEE Symposium on Security and Privacy (SP).
Differential privacy is a de facto privacy framework that has seen adoption in practice via a number of mature software platforms. Implementation of differentially private (DP) mechanisms has to be done carefully to ensure end-to-end security guarant
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c9f169feb80da35d2eee8a016cf2debb
https://doi.org/10.1109/sp46214.2022.9833672
https://doi.org/10.1109/sp46214.2022.9833672
Publikováno v:
2021 IEEE International Conference on Data Mining (ICDM).
Multi-armed bandits achieve excellent long-term performance in practice and sublinear cumulative regret in theory. However, a real-world limitation of bandit learning is poor performance in early rounds due to the need for exploration—a phenomenon
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a001fa2952d94e0b90f6aff424172fd7
https://doi.org/10.1109/icdm51629.2021.00057
https://doi.org/10.1109/icdm51629.2021.00057