Zobrazeno 1 - 10
of 47
pro vyhledávání: '"Stéphane Clinchant"'
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031282379
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7df2ebe4b6da59bfa6cace247b06b751
https://doi.org/10.1007/978-3-031-28238-6_2
https://doi.org/10.1007/978-3-031-28238-6_2
Autor:
Guglielmo Faggioli, Thibault Formal, Stefano Marchesin, Stéphane Clinchant, Nicola Ferro, Benjamin Piwowarski
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031282430
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f00468cfff4247323198c4fc31f8049b
https://hdl.handle.net/11577/3471918
https://hdl.handle.net/11577/3471918
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031282430
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ba8e95a9bbb456302a9be7e46af8a589
https://doi.org/10.1007/978-3-031-28244-7_32
https://doi.org/10.1007/978-3-031-28244-7_32
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031282430
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f2898b4445efd4a98c6136538db78213
https://doi.org/10.1007/978-3-031-28244-7_40
https://doi.org/10.1007/978-3-031-28244-7_40
Autor:
Simon Lupart, Stéphane Clinchant
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031282379
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8d7955b43b10250d34bb4d028f273428
https://doi.org/10.1007/978-3-031-28238-6_39
https://doi.org/10.1007/978-3-031-28238-6_39
Publikováno v:
Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval.
Publikováno v:
SIGIR
We propose a Composite Code Sparse Autoencoder (CCSA) approach for Approximate Nearest Neighbor (ANN) search of document representations based on Siamese-BERT models. In Information Retrieval (IR), the ranking pipeline is generally decomposed in two
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::af35a44c07594ab92cb268a1169d918a
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030997380
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9faaaa271d6f83f2002065e0fa4b7575
https://doi.org/10.1007/978-3-030-99739-7_14
https://doi.org/10.1007/978-3-030-99739-7_14
Publikováno v:
SIGIR
SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval
SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, Jul 2021, Virtual Event, Canada. pp.2288-2292, ⟨10.1145/3404835.3463098⟩
SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval
SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, Jul 2021, Virtual Event, Canada. pp.2288-2292, ⟨10.1145/3404835.3463098⟩
In neural Information Retrieval, ongoing research is directed towards improving the first retriever in ranking pipelines. Learning dense embeddings to conduct retrieval using efficient approximate nearest neighbors methods has proven to work well. Me
Autor:
Carlos Lassance, Elvin Isufi, Jean-Michel Renders, Yutong Xie, Thibaut Thonet, Michael M. Bronstein, Stéphane Clinchant, Jiaqi Ma
Publikováno v:
RecSys 2021-15th ACM Conference on Recommender Systems
RecSys
RecSys
Graph neural networks (GNNs) have recently gained significant momentum in the recommendation community, demonstrating state-of-the-art performance in top-k recommendation and next-item recommendation. Despite promising results on GNN-based recommenda
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5fe1b669cd4e1ff8d5082497f35240ed
http://resolver.tudelft.nl/uuid:50b77b37-3283-4643-aa0e-5db4678d18c6
http://resolver.tudelft.nl/uuid:50b77b37-3283-4643-aa0e-5db4678d18c6