Yves Grandvalet - en https://www.hds.utc.fr/~grandval/dokuwiki/ 2026-05-24T02:29:25+00:00 Yves Grandvalet https://www.hds.utc.fr/~grandval/dokuwiki/ https://www.hds.utc.fr/~grandval/dokuwiki/_media/wiki/dokuwiki.svg text/html 2022-09-08T07:16:36+00:00 Anonymous (anonymous@undisclosed.example.com) accueil https://www.hds.utc.fr/~grandval/dokuwiki/en/accueil?rev=1662621396&do=diff CNRS senior researcher, Heudiasyc, UMR 7253 Deputy director of Heudiasyc Member of the Section 6 « Sciences de l'information », president of the CID 55 « Sciences et données » of the CoNRS. mail: grandval[at]utc[dot]fr tel: 33(0)3 44 23 49 28 fax: 33(0)3 44 23 44 77 office: GI 219 Université de technologie de Compiègne, text/html 2014-07-07T10:05:26+00:00 Anonymous (anonymous@undisclosed.example.com) agenda https://www.hds.utc.fr/~grandval/dokuwiki/en/agenda?rev=1404727526&do=diff <html> <iframe src=“<https://www.google.com/calendar/embed?height=600&amp;wkst=1&amp;bgcolor=%23FFFFFF&amp;src=r62cgjbrqdev3h2nk14451lvrs%40group.calendar.google.com&amp;color=%232952A3&amp;ctz=Europe%2FParis>” style=“ border-width:0 ” width=“800” height=“600” frameborder=“0” scrolling=“no”></iframe> </html> text/html 2023-09-01T08:05:16+00:00 Anonymous (anonymous@undisclosed.example.com) articles https://www.hds.utc.fr/~grandval/dokuwiki/en/articles?rev=1693555516&do=diff Selected Papers by Theme Penalization & Sparsity * Sanchez Merchante, L. F. and Grandvalet, Y. and Govaert, G. An Efficient Approach to Sparse Linear Discriminant Analysis 29th International Conference on Machine Learning (ICML 2012) pp. 1167-1174, 2012. * Szafranski, M. and Grandvalet, Y. and Rakotomamonjy, A. text/html 2023-09-01T08:03:13+00:00 Anonymous (anonymous@undisclosed.example.com) code https://www.hds.utc.fr/~grandval/dokuwiki/en/code?rev=1693555393&do=diff Online Code These pieces of code are provided for facilitating dissemination and reproduction of published experimental results. Any bug report is welcomed, but please refrain to ask for some installation support from the authors. As usual, these codes are provided text/html 2018-04-05T12:01:47+00:00 Anonymous (anonymous@undisclosed.example.com) projects https://www.hds.utc.fr/~grandval/dokuwiki/en/projects?rev=1522929707&do=diff European Projects MASH The MASH project investigates the design of complex learning systems to increase the performance of artificial intelligence. To create such systems, we want to involve large groups of contributors from as many fields and backgrounds as possible, to program large and heterogeneous families of feature extraction modules. text/html 2007-01-10T10:40:10+00:00 Anonymous (anonymous@undisclosed.example.com) publi https://www.hds.utc.fr/~grandval/dokuwiki/en/publi?rev=1168425610&do=diff <phpinc=publications_en.php> text/html 2018-03-06T10:28:04+00:00 Anonymous (anonymous@undisclosed.example.com) publis_hal https://www.hds.utc.fr/~grandval/dokuwiki/en/publis_hal?rev=1520332084&do=diff text/html 2023-08-31T14:48:07+00:00 Anonymous (anonymous@undisclosed.example.com) research https://www.hds.utc.fr/~grandval/dokuwiki/en/research?rev=1693493287&do=diff Research Interests Supervised and unsupervised learning, Statistical Pattern Recognition, Flexible regression/discrimination/clustering techniques. Keywords Sparsity Inducing Penalties, Representation learning, Co-Clustering, Cross-Validation, Semi-supervised learning, Noise Injection, Evidential Pattern Recognition, Bioinformatics, Fault Diagnosis & Environmental Monitoring. text/html 2023-08-17T13:56:18+00:00 Anonymous (anonymous@undisclosed.example.com) sidebar https://www.hds.utc.fr/~grandval/dokuwiki/en/sidebar?rev=1692280578&do=diff Welcome Research Papers Online Publications Softwares Projects text/html 2022-07-21T07:03:48+00:00 Anonymous (anonymous@undisclosed.example.com) start https://www.hds.utc.fr/~grandval/dokuwiki/en/start?rev=1658387028&do=diff CNRS senior researcher, Heudiasyc, UMR 7253 Deputy director of Heudiasyc Member of the Section 6 « Sciences de l'information », president of the CID 55 « Sciences et données » of the CoNRS. mail: grandval[at]utc[dot]fr tel: 33(0)3 44 23 49 28 fax: 33(0)3 44 23 44 77 office: GI 219 Université de technologie de Compiègne,