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Gaëlle Bonnet-Loosli – Research and Teaching activities

Research and Teaching activities

http://gaelle.loosli.fr/

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Gaëlle Bonnet-Loosli – Research and Teaching activities | gaelle.loosli.fr Reviews

https://gaelle.loosli.fr

Research and Teaching activities

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novembre 2013 – Gaëlle Bonnet-Loosli

http://gaelle.loosli.fr/2013/11

Research and Teaching activities. Learning SVM in Krein Spaces. Using SVDD in SimpleMKL for 3D-Shapes Filtering. 3D shape retrieval using uncertain semantic query: a preliminary study. Multimodal quantification and validation of 3D regional myocardial function. This ANR project started in 2011 for 48 months. I’m working on the data normalization part. Here is a presentation I did, before we have any real data, giving hints on what we could do (in french). Read more. P Bouges, T Chateau, C Blanc, G Loosli.

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juin 2014 – Gaëlle Bonnet-Loosli

http://gaelle.loosli.fr/2014/06

Research and Teaching activities. Learning SVM in Krein Spaces. Using SVDD in SimpleMKL for 3D-Shapes Filtering. 3D shape retrieval using uncertain semantic query: a preliminary study. Is a subproject of MASTODONS. Here is the introduction of the project:. Using SVDD in SimpleMKL for 3D-Shapes Filtering. To be published at CAp 2014 conference. In Saint-Etienne, France. Authors: Gaëlle Loosli and Hattoibe Aboubacar.

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3D shape retrieval using uncertain semantic query: a preliminary study – Gaëlle Bonnet-Loosli

http://gaelle.loosli.fr/3d-shape-retrieval-using-uncertain-semantic-query-a-preliminary-study

Research and Teaching activities. Learning SVM in Krein Spaces. Using SVDD in SimpleMKL for 3D-Shapes Filtering. 3D shape retrieval using uncertain semantic query: a preliminary study. 3D shape retrieval using uncertain semantic query: a preliminary study. This paper was accepted as a short paper and presented by Hattoibe Aboubacar at ICPRAM 2014. Authors : Hattoibe ABOUBACAR,Vincent BARRA, Gae lle LOOSLI. Sur le même thème. Using SVDD in SimpleMKL for 3D-Shapes Filtering.

4

Petasky – Gaëlle Bonnet-Loosli

http://gaelle.loosli.fr/petasky

Research and Teaching activities. Learning SVM in Krein Spaces. Using SVDD in SimpleMKL for 3D-Shapes Filtering. 3D shape retrieval using uncertain semantic query: a preliminary study. Is a subproject of MASTODONS. Here is the introduction of the project:. I’m implied in the Data-Mining and Machine Learning team in the Petasky project and currently work on the redshift evaluation. Sur le même thème. Learning SVM in Krein Spaces. Using SVDD in SimpleMKL for 3D-Shapes Filtering.

5

Gaelle – Gaëlle Bonnet-Loosli

http://gaelle.loosli.fr/author/gaelle

Research and Teaching activities. Learning SVM in Krein Spaces. Using SVDD in SimpleMKL for 3D-Shapes Filtering. 3D shape retrieval using uncertain semantic query: a preliminary study. Learning SVM in Krein Spaces. Our paper on SVMs in Krein Spaces. Authors: Gaëlle Loosli, Stéphane Canu and Cheng Ong Soon. Read more. Is a subproject of MASTODONS. Here is the introduction of the project:. Using SVDD in SimpleMKL for 3D-Shapes Filtering. To be published at CAp 2014 conference. In Saint-Etienne, France.

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projects:infimnist [leon.bottou.org]

http://leon.bottou.org/projects/infimnist

The infinite MNIST dataset. 3 Download and Compilation. 4 Using the InfiMNIST executable. 5 Using InfiMNIST as a library. The infinite MNIST dataset. This code produces an infinite supply of digit images derived from the well known MNIST dataset using pseudo-random deformations and translations. This is a streamlined version of the code used for the experiments reported in (Loosli, Canu, Bottou, 2007). Is generated by applying a pseudorandom transformation to the MNIST training example numbered. Contains...

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Gaëlle Bonnet-Loosli – Research and Teaching activities

Research and Teaching activities. Aiolli et al., 2017. Aiolli, F., Bonnet-Loosli, G., and Hérault, R. (2017). Advances in artificial neural networks, machine learning and computational intelligence. 268:1–3. Editorial. [ bib. Loosli, G. (2016). Study on the loss of information caused by the positivation of graph kernels for 3d shapes. In. 24th European Symposium on Artificial Neural Networks Bruges, Belgium, April 27-28-29. And is an approximation of the other one, which is indefinite (. Canu, S., Fo...

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