Nicolas Ballas
Nicolas Ballas
Facebook AI Research
Потвърден имейл адрес: fb.com
Fitnets: Hints for thin deep nets
A Romero, N Ballas, SE Kahou, A Chassang, C Gatta, Y Bengio
arXiv preprint arXiv:1412.6550, 2014
A closer look at memorization in deep networks
D Arpit, S Jastrzębski, N Ballas, D Krueger, E Bengio, MS Kanwal, ...
International conference on machine learning, 233-242, 2017
Describing Videos by Exploiting Temporal Structure
L Yao, A Torabi, K Cho, N Ballas, C Pal, H Larochelle, A Courville
arXiv preprint arXiv:1502.08029, 2015
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
Delving deeper into convolutional networks for learning video representations
N Ballas, L Yao, C Pal, A Courville
arXiv preprint arXiv:1511.06432, 2015
Recurrent batch normalization
T Cooijmans, N Ballas, C Laurent, Ç Gülçehre, A Courville
arXiv preprint arXiv:1603.09025, 2016
Three factors influencing minima in sgd
S Jastrzębski, Z Kenton, D Arpit, N Ballas, A Fischer, Y Bengio, A Storkey
arXiv preprint arXiv:1711.04623, 2017
Zoneout: Regularizing rnns by randomly preserving hidden activations
D Krueger, T Maharaj, J Kramár, M Pezeshki, N Ballas, NR Ke, A Goyal, ...
arXiv preprint arXiv:1606.01305, 2016
Stochastic gradient push for distributed deep learning
M Assran, N Loizou, N Ballas, M Rabbat
International Conference on Machine Learning, 344-353, 2019
A dissection of overfitting and generalization in continuous reinforcement learning
A Zhang, N Ballas, J Pineau
arXiv preprint arXiv:1806.07937, 2018
Improved conditional vrnns for video prediction
L Castrejon, N Ballas, A Courville
Proceedings of the IEEE/CVF international conference on computer vision …, 2019
Slowmo: Improving communication-efficient distributed sgd with slow momentum
J Wang, V Tantia, N Ballas, M Rabbat
arXiv preprint arXiv:1910.00643, 2019
Masked siamese networks for label-efficient learning
M Assran, M Caron, I Misra, P Bojanowski, F Bordes, P Vincent, A Joulin, ...
European Conference on Computer Vision, 456-473, 2022
Dynamic capacity networks
A Almahairi, N Ballas, T Cooijmans, Y Zheng, H Larochelle, A Courville
International Conference on Machine Learning, 2549-2558, 2016
Semi-supervised learning of visual features by non-parametrically predicting view assignments with support samples
M Assran, M Caron, I Misra, P Bojanowski, A Joulin, N Ballas, M Rabbat
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021
Residual connections encourage iterative inference
S Jastrzębski, D Arpit, N Ballas, V Verma, T Che, Y Bengio
arXiv preprint arXiv:1710.04773, 2017
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
On the relation between the sharpest directions of DNN loss and the SGD step length
S Jastrzębski, Z Kenton, N Ballas, A Fischer, Y Bengio, A Storkey
arXiv preprint arXiv:1807.05031, 2018
A dataset and exploration of models for understanding video data through fill-in-the-blank question-answering
T Maharaj, N Ballas, A Rohrbach, A Courville, C Pal
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017
Deep nets don't learn via memorization
D Krueger, N Ballas, S Jastrzebski, D Arpit, MS Kanwal, T Maharaj, ...
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