Zobrazeno 1 - 10
of 4 641
pro vyhledávání: '"De Meulemeester AS"'
Autor:
Irambona, Estelle Valentine
Publikováno v:
b-Arbitra; August 2024, Vol. 2024 Issue: 1 p285-287, 3p
Autor:
Gollub, Siegfried
Rezension zu: Johnny De Meulemeester, De Verzamelingen van de Oudheidkundige Kring van het Land van Waas in het museum te Sint-Niklaas (van de Bronstijd tot de Merovingische tijd). Nationaal Centrum voor Oudheidkundige Navorsingen in Belgie, Reeks B,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::226bbaf8aaee16b0aea90198b774feb1
We propose a unifying setting that combines existing restricted kernel machine methods into a single primal-dual multi-view framework for kernel principal component analysis in both supervised and unsupervised settings. We derive the primal and dual
Externí odkaz:
http://arxiv.org/abs/2305.17251
In this paper, we propose a kernel principal component analysis model for multi-variate time series forecasting, where the training and prediction schemes are derived from the multi-view formulation of Restricted Kernel Machines. The training problem
Externí odkaz:
http://arxiv.org/abs/2301.09811
Publikováno v:
b-Arbitra; October 2023, Vol. 2023 Issue: 1 p383-384, 2p
Autor:
Schreurs, Joachim, De Meulemeester, Hannes, Fanuel, Michaël, De Moor, Bart, Suykens, Johan A. K.
Commonly, machine learning models minimize an empirical expectation. As a result, the trained models typically perform well for the majority of the data but the performance may deteriorate in less dense regions of the dataset. This issue also arises
Externí odkaz:
http://arxiv.org/abs/2104.02373
Autor:
De Meulemeester, Hannes, Schreurs, Joachim, Fanuel, Michaël, De Moor, Bart, Suykens, Johan A. K.
Generative Adversarial Networks (GANs) are performant generative methods yielding high-quality samples. However, under certain circumstances, the training of GANs can lead to mode collapse or mode dropping, i.e. the generative models not being able t
Externí odkaz:
http://arxiv.org/abs/2006.09096
Autor:
Brian Dewar, Stephanie Chevrier, Julie De Meulemeester, Mark Fedyk, Rosendo Rodriguez, Simon Kitto, Raphael Saginur, Michel Shamy
Publikováno v:
Trials, Vol 24, Iss 1, Pp 1-12 (2023)
Abstract Introduction Equipoise, generally defined as uncertainty about the relative effects of the treatments being compared in a trial, is frequently referenced as an ethical standard for the conduct of randomized clinical trials. However, it seems
Externí odkaz:
https://doaj.org/article/919522d9f43a41539889c865e7a587e8