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Xavier Bouthillier
Xavier Bouthillier
Dirección de correo verificada de umontreal.ca - Página principal
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Theano: A Python framework for fast computation of mathematical expressions
R Al-Rfou, G Alain, A Almahairi, C Angermueller, D Bahdanau, N Ballas, ...
arXiv e-prints, arXiv: 1605.02688, 2016
1146*2016
Emonets: Multimodal deep learning approaches for emotion recognition in video
SE Kahou, X Bouthillier, P Lamblin, C Gulcehre, V Michalski, K Konda, ...
Journal on Multimodal User Interfaces 10, 99-111, 2016
4842016
Combining modality specific deep neural networks for emotion recognition in video
SE Kahou, C Pal, X Bouthillier, P Froumenty, Ç Gülçehre, R Memisevic, ...
Proceedings of the 15th ACM on International conference on multimodal …, 2013
4242013
Dropout as data augmentation
X Bouthillier, K Konda, P Vincent, R Memisevic
arXiv preprint arXiv:1506.08700, 2015
150*2015
Accounting for variance in machine learning benchmarks
X Bouthillier, P Delaunay, M Bronzi, A Trofimov, B Nichyporuk, J Szeto, ...
Proceedings of Machine Learning and Systems 3, 747-769, 2021
1292021
Fast approximate natural gradient descent in a kronecker factored eigenbasis
T George, C Laurent, X Bouthillier, N Ballas, P Vincent
Advances in Neural Information Processing Systems 31, 2018
1242018
Unreproducible research is reproducible
X Bouthillier, C Laurent, P Vincent
International Conference on Machine Learning, 725-734, 2019
972019
Efficient exact gradient update for training deep networks with very large sparse targets
P Vincent, A De Brébisson, X Bouthillier
Advances in Neural Information Processing Systems 28, 2015
662015
Survey of machine-learning experimental methods at NeurIPS2019 and ICLR2020
X Bouthillier, G Varoquaux
Inria Saclay Ile de France, 2020
562020
Oríon-asynchronous distributed hyperparameter optimization
X Bouthillier, C Tsirigotis, F Corneau-Tremblay, P Delaunay, ...
October, 2019
13*2019
An evaluation of fisher approximations beyond kronecker factorization
C Laurent, T George, X Bouthillier, N Ballas, P Vincent
32018
Exact gradient updates in time independent of output size for the spherical loss family
P Vincent, A de Brébisson, X Bouthillier
arXiv preprint arXiv:1606.08061, 2016
32016
Accounting for variance and hyperparameter optimization in machine learning benchmarks
X Bouthillier
2022
Improving Reproducibility of Benchmarks
X Bouthillier
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Artículos 1–14