Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Rhicheek Patra"'
Autor:
François Taïani, Rhicheek Patra, Rachid Guerraoui, Anne-Marie Kermarrec, Vlad Nitu, Georgios Damaskinos
Publikováno v:
Proceedings of the 21st International Middleware Conference
Middleware '20: Proceedings of the 21st International Middleware Conference
21st International Middleware Conference
21st International Middleware Conference, Nov 2020, Delft (virtual), Netherlands. ⟨10.1145/3423211.3425685⟩
Middleware 2020-21st ACM/IFIP International Middleware Conference
Middleware 2020-21st ACM/IFIP International Middleware Conference, Nov 2020, Delft (virtual), Netherlands. pp.1-16, ⟨10.1145/3423211.3425685⟩
ACM Transactions on Intelligent Systems and Technology
ACM Transactions on Intelligent Systems and Technology, 2022, 13 (5), pp.1-30. ⟨10.1145/3527621⟩
Middleware
Middleware '20: Proceedings of the 21st International Middleware Conference
21st International Middleware Conference
21st International Middleware Conference, Nov 2020, Delft (virtual), Netherlands. ⟨10.1145/3423211.3425685⟩
Middleware 2020-21st ACM/IFIP International Middleware Conference
Middleware 2020-21st ACM/IFIP International Middleware Conference, Nov 2020, Delft (virtual), Netherlands. pp.1-16, ⟨10.1145/3423211.3425685⟩
ACM Transactions on Intelligent Systems and Technology
ACM Transactions on Intelligent Systems and Technology, 2022, 13 (5), pp.1-30. ⟨10.1145/3527621⟩
Middleware
Federated learning (FL) is very appealing for its privacy benefits: essentially, a global model is trained with updates computed on mobile devices while keeping the data of users local. Standard FL infrastructures are however designed to have no ener
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::aaa06af9f0cb11b793062e793ef1987b
http://arxiv.org/abs/2006.07273
http://arxiv.org/abs/2006.07273
Publikováno v:
EURO-PAR 2019-European Conference on Parallel Processing
EURO-PAR 2019-European Conference on Parallel Processing, Aug 2019, Gottingen, Germany. pp.227-240, ⟨10.1007/978-3-030-29400-7_17⟩
Lecture Notes in Computer Science ISBN: 9783030293994
Euro-Par
EURO-PAR 2019-European Conference on Parallel Processing, Aug 2019, Gottingen, Germany. pp.227-240, ⟨10.1007/978-3-030-29400-7_17⟩
Lecture Notes in Computer Science ISBN: 9783030293994
Euro-Par
Recommenders personalize the web content using collaborative filtering to relate users (or items). This work proposes to unify user-based, item-based and neural word embeddings types of recommenders under a single abstraction for their input, we name
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1dc9d18983f32fe8077e7fa78a6e9bbf
https://hal.science/hal-02153388/document
https://hal.science/hal-02153388/document
Publikováno v:
GRADES/NDA@SIGMOD/PODS
Entity Linking, the task of mapping ambiguous Named Entities to unique identifiers in a knowledge base, is a cornerstone of multiple Information Retrieval and Text Analysis systems. So far, no single entity linking algorithm has been able to offer th
Publikováno v:
DSN 2017-The 47th IEEE/IFIP International Conference on Dependable Systems and Networks
DSN 2017-The 47th IEEE/IFIP International Conference on Dependable Systems and Networks, Jun 2017, Denver, United States. pp.1-12, ⟨10.1109/DSN.2017.22⟩
DSN
DSN 2017-The 47th IEEE/IFIP International Conference on Dependable Systems and Networks, Jun 2017, Denver, United States. pp.1-12, ⟨10.1109/DSN.2017.22⟩
DSN
Recommenders widely use collaborative filtering schemes. These schemes, however, threaten privacy as user profiles are made available to the service provider hosting the recommender and can even be guessed by curious users who analyze the recommendat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7440a4f70581a65e6711bc0cdd1f444d
https://inria.hal.science/hal-01660734
https://inria.hal.science/hal-01660734
Publikováno v:
Proceedings of the VLDB Endowment (PVLDB)
Proceedings of the VLDB Endowment (PVLDB), 2017, 10 (10), pp.1070-1081. ⟨10.14778/3115404.3115412⟩
Proceedings of the VLDB Endowment (PVLDB), VLDB Endowment, 2017, 10 (10), pp.1070-1081. ⟨10.14778/3115404.3115412⟩
Proceedings of the VLDB Endowment (PVLDB), 2017, 10 (10), pp.1070-1081. ⟨10.14778/3115404.3115412⟩
Proceedings of the VLDB Endowment (PVLDB), VLDB Endowment, 2017, 10 (10), pp.1070-1081. ⟨10.14778/3115404.3115412⟩
Recommenders, as widely implemented nowadays by major e-commerce players like Netflix or Amazon, use collaborative filtering to suggest the most relevant items to their users. Clearly, the effectiveness of recommenders depends on the data they can ex
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::550a0b811ef1f26c87c1164eb7d112d2
https://hal.inria.fr/hal-01660746
https://hal.inria.fr/hal-01660746
Publikováno v:
ICDE
Similarity computations are crucial in various web activities like advertisements, search or trust-distrust predictions. These similarities often vary with time as product perception and popularity constantly change with users' evolving inclination.
Publikováno v:
INFOCOM
Aggregation of streamed data is key to the expansion of the Internet of Things. This paper addresses the problem of designing a topology for reliably aggregating data flows from many devices arriving at a datacenter. Reliability here means ensuring o
Publikováno v:
Proceedings of the VLDB Endowment (PVLDB)
Proceedings of the VLDB Endowment (PVLDB), 2015, 8 (8), pp.862-873. ⟨10.14778/2757807.2757811⟩
Proceedings of the VLDB Endowment (PVLDB), VLDB Endowment, 2015, 8 (8), pp.862-873. ⟨10.14778/2757807.2757811⟩
Proceedings of the VLDB Endowment (PVLDB), 2015, 8 (8), pp.862-873. ⟨10.14778/2757807.2757811⟩
Proceedings of the VLDB Endowment (PVLDB), VLDB Endowment, 2015, 8 (8), pp.862-873. ⟨10.14778/2757807.2757811⟩
The upsurge in the number of web users over the last two decades has resulted in a significant growth of online information. This information growth calls for recommenders that personalize the information proposed to each individual user. Nevertheles
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5e637df860ce665029d223fa410ef0c9
https://hal.inria.fr/hal-01183859
https://hal.inria.fr/hal-01183859
Publikováno v:
Middleware 2014
Middleware 2014, Dec 2014, Bordeaux, France. ⟨10.1145/2663165.2663315⟩
Middleware
Middleware 2014, Dec 2014, Bordeaux, France. ⟨10.1145/2663165.2663315⟩
Middleware
International audience; The ever-growing amount of data available on the Internet calls for personalization. Yet, the most effective personalization schemes, such as those based on collaborative filtering (CF), are notoriously resource greedy. This p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0f66c6be30b9a4d7be056eaf983fa805
https://inria.hal.science/hal-01080016/document
https://inria.hal.science/hal-01080016/document