Zobrazeno 1 - 10
of 56
pro vyhledávání: '"NGuyen, Kim Thang"'
Autor:
Kevi, Enikő, Nguyen, Kim-Thang
Designing online algorithms with machine learning predictions is a recent technique beyond the worst-case paradigm for various practically relevant online problems (scheduling, caching, clustering, ski rental, etc.). While most previous learning-augm
Externí odkaz:
http://arxiv.org/abs/2312.14564
Publikováno v:
In Theoretical Computer Science 21 September 2022 930:209-217
Akademický článek
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Autor:
Davy Catherine A., Nguyen Kim Thang, Song Yang, Troadec David, Blanchenet Anne-Marie, Adler Pierre M.
Publikováno v:
EPJ Web of Conferences, Vol 140, p 12016 (2017)
The pore structure of a natural shale is obtained by three imaging means. Micro-tomography results are extended to provide the spatial arrangement of the minerals and pores present at a voxel size of 700 nm (the macroscopic scale). FIB/SEM provides a
Externí odkaz:
https://doaj.org/article/c3f0d04cdb80464ca93b5afa27a4b881
Autor:
Marek Chrobak, Łukasz Jeż, Nguyen Kim Thang, Martin Böhm, Pavel Veselý, Jiří Sgall, Christoph Dürr, Jaroslaw Byrka, Marcin Bienkowski, Lukáš Folwarczný
Publikováno v:
Theoretical Computer Science
Theoretical Computer Science, Elsevier, 2021, 861, pp.133-143. ⟨10.1016/j.tcs.2021.02.016⟩
Theoretical Computer Science, 2021, 861, pp.133-143. ⟨10.1016/j.tcs.2021.02.016⟩
Theoretical Computer Science, Elsevier, 2021, 861, pp.133--143. ⟨10.1016/j.tcs.2021.02.016⟩
Theoretical Computer Science, Elsevier, 2021, 861, pp.133-143. ⟨10.1016/j.tcs.2021.02.016⟩
Theoretical Computer Science, 2021, 861, pp.133-143. ⟨10.1016/j.tcs.2021.02.016⟩
Theoretical Computer Science, Elsevier, 2021, 861, pp.133--143. ⟨10.1016/j.tcs.2021.02.016⟩
In the Multi-Level Aggregation Problem ( MLAP ), requests for service arrive at the nodes of an edge-weighted rooted tree T . Each service is represented by a subtree X of T that contains its root. This subtree X serves all requests that are pending
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0186c04d6bcce26ca5e147e16ac11595
https://hal.archives-ouvertes.fr/hal-03377715
https://hal.archives-ouvertes.fr/hal-03377715
Publikováno v:
Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}
Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence, Jan 2021, Yokohama, Japan. pp.2148--2154, ⟨10.24963/ijcai.2020/297⟩
Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}, Jan 2021, Yokohama, Japan. pp.2148--2154, ⟨10.24963/ijcai.2020/297⟩
IJCAI
Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence, Jan 2021, Yokohama, Japan. pp.2148--2154, ⟨10.24963/ijcai.2020/297⟩
Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}, Jan 2021, Yokohama, Japan. pp.2148--2154, ⟨10.24963/ijcai.2020/297⟩
IJCAI
International audience; Many real-world problems can often be cast as the optimization of DR-submodular functions defined over a convex domain. These functions play an important role with applications in many areas of applied mathematics, such as mac
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f79ae0b92a07fd5bf39670cf4c4ee991
https://hal.archives-ouvertes.fr/hal-02980471
https://hal.archives-ouvertes.fr/hal-02980471
Autor:
Nguyen, Kim Thang
Publikováno v:
34th Conference on Neural Information Processing Systems (NeurIPS 2020)
34th Conference on Neural Information Processing Systems (NeurIPS 2020), Dec 2020, Virtual Conference, Canada
34th Conference on Neural Information Processing Systems (NeurIPS 2020), Dec 2020, Virtual Conference, Canada
International audience; We consider online bandit learning in which at every time step, an algorithm has to make a decision and then observe only its reward. The goal is to design efficient (polynomial-time) algorithms that achieve a total reward app
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::9e43f9614e08989c353230dfa46e7466
https://hal.archives-ouvertes.fr/hal-03277640
https://hal.archives-ouvertes.fr/hal-03277640
Akademický článek
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Publikováno v:
Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering ISBN: 9783030630829
INISCOM
INISCOM
This paper proposes a new method of distributed watermarking for large image database that is used for deep learning. We detect the semantic meaning of set of images from the database and embed the a part of watermark into such images set. A part of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::87e0a6b5a3c700fe09c93aa9326737ce
https://doi.org/10.1007/978-3-030-63083-6_13
https://doi.org/10.1007/978-3-030-63083-6_13
Autor:
Lucarelli, Giorgio, Moseley, Benjamin, Nguyen, Kim Thang, Srivastav, Abhinav, Trystram, Denis
Publikováno v:
39th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2019)
39th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2019), Dec 2019, Bombay, India
14th Workshop on Models and Algorithms for Planning and Scheduling Problems (MAPSP 2019)
14th Workshop on Models and Algorithms for Planning and Scheduling Problems (MAPSP 2019), Jun 2019, Renesse, Netherlands
39th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2019), Dec 2019, Bombay, India
14th Workshop on Models and Algorithms for Planning and Scheduling Problems (MAPSP 2019)
14th Workshop on Models and Algorithms for Planning and Scheduling Problems (MAPSP 2019), Jun 2019, Renesse, Netherlands
International audience; We consider the problem of scheduling jobs to minimize the maximum weighted flow-timeon a set of related machines. When jobs can be preempted this problem is well-understood; forexample, there exists a constant competitive alg
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4900b5005ba735ab449d60352bfeeef7
https://hal.archives-ouvertes.fr/hal-02416965
https://hal.archives-ouvertes.fr/hal-02416965