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Soufiane Hayou
Soufiane Hayou
Simons Institute for the Theory of Computing, UC Berkeley (On Leave from NUS)
Verified email at berkeley.edu - Homepage
Title
Cited by
Cited by
Year
On the impact of the activation function on deep neural networks training
S Hayou, A Doucet, J Rousseau
36th International Conference on Machine Learning (ICML 2019), 2019
2172019
On the selection of initialization and activation function for deep neural networks
S Hayou, A Doucet, J Rousseau
arXiv preprint arXiv:1805.08266, 2018
842018
Stable ResNet
S Hayou, E Clerico, B He, G Deligiannidis, A Doucet, J Rousseau
24th International Conference on Artificial Intelligence and Statistics …, 2021
412021
Robust Pruning at Initialization
S Hayou, JF Ton, A Doucet, YW Teh
International Conference on Learning Representations (ICLR 2021), 2021
402021
Mean-field Behaviour of Neural Tangent Kernel for Deep Neural Networks
S Hayou, A Doucet, J Rousseau
arXiv preprint arXiv:1905.13654, 2019
262019
On the impact of the activation function on deep neural networks training
H Soufiane, D Arnaud, R Judith
Proceedings of the 36 th International Conference on Machine Learning, Long …, 2019
16*2019
On the infinite-depth limit of finite-width neural networks
S Hayou
Transactions on Machine Learning Research (arXiv:2210.00688), 2022
142022
Feature learning and signal propagation in deep neural networks
Y Lou, CE Mingard, S Hayou
International Conference on Machine Learning, 14248-14282, 2022
122022
Pruning untrained neural networks: Principles and analysis
S Hayou, JF Ton, A Doucet, Y Whye Teh
arXiv e-prints, arXiv: 2002.08797, 2020
122020
Training dynamics of deep networks using stochastic gradient descent via neural tangent kernel
S Hayou, A Doucet, J Rousseau
arXiv preprint arXiv:1905.13654, 2019
122019
Regularization in ResNet with Stochastic Depth
S Hayou, F Ayed
NeurIPS 2021, arXiv:2106.03091, 2021
92021
Width and Depth Limits Commute in Residual Networks
S Hayou, G Yang
ICML 2023 (arXiv preprint arXiv:2302.00453), 2023
62023
The curse of depth in kernel regime
S Hayou, A Doucet, J Rousseau
I (Still) Can't Believe It's Not Better! Workshop at NeurIPS 2021, 41-47, 2022
52022
Connecting Optimization and Generalization via Gradient Flow Path Length
F Liu, H Yang, S Hayou, Q Li
arXiv preprint arXiv:2202.10670, 2022
42022
Tensor Programs VI: Feature Learning in Infinite-Depth Neural Networks
G Yang, D Yu, C Zhu, S Hayou
ICLR 2024, 2023
22023
Leave-one-out distinguishability in machine learning
J Ye, A Borovykh, S Hayou, R Shokri
ICLR 2024, arXiv preprint arXiv:2309.17310, 2023
22023
Data pruning and neural scaling laws: fundamental limitations of score-based algorithms
F Ayed, S Hayou
Transactions on Machine Learning Research 2023. (arXiv preprint arXiv:2302 …, 2023
22023
Probabilistic fine-tuning of pruning masks and PAC-Bayes self-bounded learning
S Hayou, B He, GK Dziugaite
arXiv preprint arXiv:2110.11804, 2021
22021
On the selection of initialization and activation function for deep neural networks. CoRR abs/1805.08266 (2018)
S Hayou, A Doucet, J Rousseau
arXiv preprint arXiv:1805.08266, 1805
21805
Feature Learning in Infinite Depth Neural Networks
G Yang, D Yu, C Zhu, S Hayou
The Twelfth International Conference on Learning Representations, 2023
12023
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