Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Crulis, Ben"'
Current artificial neural networks are trained with parameters encoded as floating point numbers that occupy lots of memory space at inference time. Due to the increase in the size of deep learning models, it is becoming very difficult to consider tr
Externí odkaz:
http://arxiv.org/abs/2408.04460
Autor:
Hoang, Lê-Nguyên, Faucon, Louis, Jungo, Aidan, Volodin, Sergei, Papuc, Dalia, Liossatos, Orfeas, Crulis, Ben, Tighanimine, Mariame, Constantin, Isabela, Kucherenko, Anastasiia, Maurer, Alexandre, Grimberg, Felix, Nitu, Vlad, Vossen, Chris, Rouault, Sébastien, El-Mhamdi, El-Mahdi
Today's large-scale algorithms have become immensely influential, as they recommend and moderate the content that billions of humans are exposed to on a daily basis. They are the de-facto regulators of our societies' information diet, from shaping op
Externí odkaz:
http://arxiv.org/abs/2107.07334
This paper addresses the problem of defining a subjective interestingness measure for BI exploration. Such a measure involves prior modeling of the belief of the user. The complexity of this problem lies in the impossibility to ask the user about the
Externí odkaz:
http://arxiv.org/abs/1907.06946
Autor:
Chanson, Alexandre, Crulis, Ben, Labroche, Nicolas, Marcel, Patrick, Peralta, Veronika, Rizzi, Stefano, Vassiliadis, Panos
Publikováno v:
Design, Optimization, Languages and Analytical Processing of Big Data
Design, Optimization, Languages and Analytical Processing of Big Data, Mar 2020, Copenhagen, Denmark
Design, Optimization, Languages and Analytical Processing of Big Data, Mar 2020, Copenhagen, Denmark
International audience; This paper introduces the Traveling Analyst Problem (TAP), an original strongly NP-hard problem where an automated algorithm assists an analyst to explore a dataset, by suggesting the most interesting and coherent set of queri
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::8110f7685a4057b342a0acf910920779
https://hdl.handle.net/11585/752107
https://hdl.handle.net/11585/752107
Publikováno v:
DOLAP 2019
DOLAP 2019, Mar 2019, Lisboa, Portugal
DOLAP 2019, Mar 2019, Lisboa, Portugal
International audience; This paper addresses the long-term problem of defining a subjective interestingness measure for BI exploration. Such a measure involves prior modeling of the belief of the user. The complexity of this problem lies in the impos
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::3579a18a1ecbb2fa85417c90e4a523db
https://hal.archives-ouvertes.fr/hal-02375871/document
https://hal.archives-ouvertes.fr/hal-02375871/document
Publikováno v:
ComplexRec 2018 Second Workshop on Recommendation in Complex Scenarios @ RecSys 2018
ComplexRec 2018 Second Workshop on Recommendation in Complex Scenarios @ RecSys 2018, Oct 2018, Vancouver, Canada
ComplexRec 2018 Second Workshop on Recommendation in Complex Scenarios @ RecSys 2018, Oct 2018, Vancouver, Canada
International audience
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::5911233fccf951f3fb0097795f5208ec
https://hal.science/hal-01898300
https://hal.science/hal-01898300