Zobrazeno 1 - 10 of 98 pro vyhledávání: '"Détection de communautés"'
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Contributions à l'apprentissage de représentations à partir d'autoencodeurs de graphes et applications à la recommandation musicale
Autor: Salha-Galvan, Guillaume
Graph autoencoders (GAE) and variational graph autoencoders (VGAE) emerged as two powerful groups of unsupervised node embedding methods, with various applications to graph-based machine learning problems such as link prediction and community detecti
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b98af421887e22d19bb632ae4e0e8951
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3
Inférence dans des grands graphes aléatoires
Autor: Stephan, Ludovic
Publikováno v: General Mathematics [math.GM]. Sorbonne Université, 2021. English. ⟨NNT : 2021SORUS497⟩
This manuscript deals with inference problems on large, usually sparse, random graphs. We first focus on a planted tree problem, where a tree with known shape is planted inside a sparse Erdös-Rényi graph. When this tree is a path, we provide a comp
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od_______165::9e9831762717247fba41d320bbf74525
https://theses.hal.science/tel-03720004/file/STEPHAN_Ludovic_2021.pdf
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4
Research and development of innovative mathematical algorithms using cluster-based interactions of metagenomic data in biomedicine
Autor: Champion, Camille
Publikováno v: Statistics [math.ST]. INSA de Toulouse, 2021. English. ⟨NNT : 2021ISAT0005⟩
Statistiques [math.ST]. Institut National des Sciences Appliquées de Toulouse, 2021. Français
The developement of new biotechnologies offers a large variety of biological datasets, extending the scope of biomedical research. These include genomic datasets, highly developed in statistical literature and metagenomic datasets, still relatively u
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::c8e40920d0caca4a45c15f854abf12d0
https://tel.archives-ouvertes.fr/tel-03395321/document
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5
atlas.brussels, un outil de géovisualisation de l’extension et de la fragmentation métropolitaine bruxelloise
Autor: Olivier Finance, Isabelle Thomas, Arnaud Adam
Publikováno v: mappemonde
mappemonde, 2021, ⟨10.4000/mappemonde.5506⟩
atlas.brussels est un outil de géovisualisation interactive en ligne qui permet de questionner l’extension spatiale et la fragmentation interne de l’aire métropolitaine bruxelloise. Pour ce faire, l’outil se focalise de manière originale sur
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4a2e2a55a1db09de648792d24aa3e6d7
https://doi.org/10.4000/mappemonde.5506
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6
Les communautés dans les multigraphes de co-appartenance : Application aux listes Twitter
Autor: Benabdelkrim, Mohamed
Graphs are mathematical tools for modelling relationships between entities. They are used in multiple scientific fields: in computer science for knowledge representation, in sociology for studying relationships between people, in chemistry for repres
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od_______166::90f63e664ce1a9f14c968b48c4edfdac
https://theses.hal.science/tel-03670875
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7
Image segmentation and extraction based on pixel communities
Autor: Nguyen, Thanh-Khoa
Publikováno v: Image Processing [eess.IV]. Université de La Rochelle, 2019. English. ⟨NNT : 2019LAROS035⟩
Image segmentation has become an indispensable task that is widely employed in several image processing applications including object detection, object tracking, automatic driver assistance, and traffic control systems, etc. The literature abounds wi
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::5ff7bdad8fb6afa1c713534a4480a158
https://tel.archives-ouvertes.fr/tel-03223157/document
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8
Équilibrage bi-stochastique des matrices pour la détection de structures par blocs et applications
Autor: Le Gorrec, Luce
Publikováno v: Réseaux et télécommunications [cs.NI]. Université Paul Sabatier-Toulouse III, 2019. Français. ⟨NNT : 2019TOU30136⟩
The detection of block structures in matrices is an important challenge. First in data analysis where matrices are a key tool for data representation, as data tables or adjacency matrices. Indeed, for the first one, finding a co-clustering is equival
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od______2592::902d315540cdbd54e9e2c585bc3462ab
https://tel.archives-ouvertes.fr/tel-02735291
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9
Exploring new geographies of interactions in and around the metropolitan area of Brussels
Autor: Adam, Arnaud
Publikováno v: Geography. Université catholique de Louvain, 2019. English
In a global effort to achieve sustainable land management, regional and urban planning call for new adaptive datasets and methods to better grasp interactions between people and places. Understanding the moves of people, freight and information, and
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od_______212::e8ace4fc16c06e240fa78f1dcb7c5868
https://tel.archives-ouvertes.fr/tel-02284406/document
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10
Complex networks based word embeddings
Autor: Victor Connes, Nicolas Dugué
Publikováno v: TALN 2019
TALN 2019, Jul 2019, Toulouse, France
HAL
Most of the time, the first step to learn word embeddings is to build a word co-occurrence matrix. As such matrices are equivalent to graphs, complex networks theory can naturally be used to deal with such data. In this paper, we consider applying co
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a7a1a1cfa72096884ec537a29251173c
https://hal.archives-ouvertes.fr/hal-02408156/document
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