Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Jacques-Henri Sublemontier"'
Federated learning enables different parties to collaboratively build a global model under the orchestration of a server while keeping the training data on clients' devices. However, performance is affected when clients have heterogeneous data. To co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::422983a13c3e7ccb8483c07e42423220
http://arxiv.org/abs/2206.08752
http://arxiv.org/abs/2206.08752
Autor:
Jacques-Henri Sublemontier
Publikováno v:
IJCNN
International Joint Conference on Neural Networks (IJCNN 2013)
International Joint Conference on Neural Networks (IJCNN 2013), IEEE-INNS, Aug 2013, Dallas, United States
International Joint Conference on Neural Networks (IJCNN 2013)
International Joint Conference on Neural Networks (IJCNN 2013), IEEE-INNS, Aug 2013, Dallas, United States
International audience; In this paper, we propose a collaborative framework that is able to solve multi-view and alternative clustering problems using some clustering ensemble and semi-supervised clustering principles. We provide a mechanism to contr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9fce57b1d2ba10d03c9253c624ac701f
https://doi.org/10.1109/ijcnn.2013.6706911
https://doi.org/10.1109/ijcnn.2013.6706911
Publikováno v:
ICDM Workshops
ICDMW 2011, The Eleventh IEEE International Conference on Data Mining Workshops
OEDM 2011, Optimization based approaches for Emerging Data Mining problems
OEDM 2011, Optimization based approaches for Emerging Data Mining problems, Dec 2011, Vancouver, Canada. pp._
ICDMW 2011, The Eleventh IEEE International Conference on Data Mining Workshops
OEDM 2011, Optimization based approaches for Emerging Data Mining problems
OEDM 2011, Optimization based approaches for Emerging Data Mining problems, Dec 2011, Vancouver, Canada. pp._
International audience; In this paper we introduce new models for semi-supervised clustering problem; in particular we address this problem from the representation space point of view. Given a dataset enhanced with constraints (typically must-link an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::720bd176a3e280cd390e5a09a26bf006
https://doi.org/10.1109/icdmw.2011.103
https://doi.org/10.1109/icdmw.2011.103
Publikováno v:
ICDM 2009, The Ninth IEEE International Conference on Data Mining
ICDM 2009, The Ninth IEEE International Conference on Data Mining, Dec 2009, Miami, United States. pp.752-757, ⟨10.1109/ICDM.2009.138⟩
ICDM
ICDM 2009, The Ninth IEEE International Conference on Data Mining, Dec 2009, Miami, United States. pp.752-757, ⟨10.1109/ICDM.2009.138⟩
ICDM
This paper deals with clustering for multi-view data, i.e. objects described by several sets of variables or proximity matrices. Many important domains or applications such as Information Retrieval, biology, chemistry and marketing are concerned by t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::94e6fc56737f56737853bbd37edb2558
https://hal.archives-ouvertes.fr/hal-00460800
https://hal.archives-ouvertes.fr/hal-00460800