Yann N. Dauphin

According to our database, Yann N. Dauphin authored at least 52 papers between 2011 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

A density estimation perspective on learning from pairwise human preferences.

Vincent Dumoulin, Daniel D. Johnson, Pablo Samuel Castro, Hugo Larochelle, Yann N. Dauphin

Trans. Mach. Learn. Res., 2024

Towards Optimal Adapter Placement for Efficient Transfer Learning.

Aleksandra Irena Nowak, Otniel-Bogdan Mercea, Anurag Arnab, Jonas Pfeiffer, Yann N. Dauphin, Utku Evci

CoRR, 2024

Neglected Hessian component explains mysteries in Sharpness regularization.

Yann N. Dauphin, Atish Agarwala, Hossein Mobahi

CoRR, 2024

2023

Temperature check: theory and practice for training models with softmax-cross-entropy losses.

Atish Agarwala, Samuel Stern Schoenholz, Jeffrey Pennington, Yann N. Dauphin

Trans. Mach. Learn. Res., 2023

Has the Machine Learning Review Process Become More Arbitrary as the Field Has Grown? The NeurIPS 2021 Consistency Experiment.

Alina Beygelzimer, Yann N. Dauphin, Percy Liang, Jennifer Wortman Vaughan

CoRR, 2023

JaxPruner: A concise library for sparsity research.

Joo Hyung Lee, Wonpyo Park, Nicole Mitchell, Jonathan Pilault, Johan S. Obando-Ceron, Han-Byul Kim, Namhoon Lee, Elias Frantar, Yun Long, Amir Yazdanbakhsh, Shivani Agrawal, Suvinay Subramanian, Xin Wang, Sheng-Chun Kao, Xingyao Zhang, Trevor Gale, Aart Bik, Woohyun Han, Milen Ferev, Zhonglin Han, Hong-Seok Kim, Yann N. Dauphin, Karolina Dziugaite, Pablo Samuel Castro, Utku Evci

CoRR, 2023

Robustmix: Improving Robustness by Regularizing the Frequency Bias of Deep Nets.

Jonas Ngnawé, Marianne Abemgnigni Njifon, Jonathan Heek, Yann N. Dauphin

CoRR, 2023

Tied-Augment: Controlling Representation Similarity Improves Data Augmentation.

Emirhan Kurtulus, Zichao Li, Yann N. Dauphin, Ekin Dogus Cubuk

Proceedings of the International Conference on Machine Learning, 2023

SAM operates far from home: eigenvalue regularization as a dynamical phenomenon.

Atish Agarwala, Yann N. Dauphin

Proceedings of the International Conference on Machine Learning, 2023

2022

How do Authors' Perceptions of their Papers Compare with Co-authors' Perceptions and Peer-review Decisions?

Charvi Rastogi, Ivan Stelmakh, Alina Beygelzimer, Yann N. Dauphin, Percy Liang, Jennifer Wortman Vaughan, Zhenyu Xue, Hal Daumé III, Emma Pierson, Nihar B. Shah

CoRR, 2022

No One Representation to Rule Them All: Overlapping Features of Training Methods.

Raphael Gontijo Lopes, Yann N. Dauphin, Ekin Dogus Cubuk

Proceedings of the Tenth International Conference on Learning Representations, 2022

Gradient Flow in Sparse Neural Networks and How Lottery Tickets Win.

Utku Evci, Yani Ioannou, Cem Keskin, Yann N. Dauphin

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Continental-Scale Building Detection from High Resolution Satellite Imagery.

Wojciech Sirko, Sergii Kashubin, Marvin Ritter, Abigail Annkah, Yasser Salah Eddine Bouchareb, Yann N. Dauphin, Daniel Keysers, Maxim Neumann, Moustapha Cissé, John Quinn

CoRR, 2021

Auxiliary Task Update Decomposition: the Good, the Bad and the neutral.

Lucio M. Dery, Yann N. Dauphin, David Grangier

Proceedings of the 9th International Conference on Learning Representations, 2021

Deconstructing the Regularization of BatchNorm.

Yann N. Dauphin, Ekin Dogus Cubuk

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Robust and On-the-fly Dataset Denoising for Image Classification.

Jiaming Song, Lunjia Hu, Yann N. Dauphin, Michael Auli, Tengyu Ma

CoRR, 2020

Robust and On-the-Fly Dataset Denoising for Image Classification.

Jiaming Song, Yann N. Dauphin, Michael Auli, Tengyu Ma

Proceedings of the Computer Vision - ECCV 2020, 2020

2019

Selective Brain Damage: Measuring the Disparate Impact of Model Pruning.

Sara Hooker, Aaron C. Courville, Yann N. Dauphin, Andrea Frome

CoRR, 2019

Simple and Effective Noisy Channel Modeling for Neural Machine Translation.

Kyra Yee, Nathan Ng, Yann N. Dauphin, Michael Auli

CoRR, 2019

MetaInit: Initializing learning by learning to initialize.

Yann N. Dauphin, Samuel S. Schoenholz

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Fixup Initialization: Residual Learning Without Normalization.

Hongyi Zhang, Yann N. Dauphin, Tengyu Ma

Proceedings of the 7th International Conference on Learning Representations, 2019

Pay Less Attention with Lightweight and Dynamic Convolutions.

Felix Wu, Angela Fan, Alexei Baevski, Yann N. Dauphin, Michael Auli

Proceedings of the 7th International Conference on Learning Representations, 2019

Simple and Effective Noisy Channel Modeling for Neural Machine Translation.

Kyra Yee, Yann N. Dauphin, Michael Auli

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

On the Pitfalls of Measuring Emergent Communication.

Ryan Lowe, Jakob N. Foerster, Y-Lan Boureau, Joelle Pineau, Yann N. Dauphin

Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019

Strategies for Structuring Story Generation.

Angela Fan, Mike Lewis, Yann N. Dauphin

Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

2018

mixup: Beyond Empirical Risk Minimization.

Hongyi Zhang, Moustapha Cissé, Yann N. Dauphin, David Lopez-Paz

Proceedings of the 6th International Conference on Learning Representations, 2018

Empirical Analysis of the Hessian of Over-Parametrized Neural Networks.

Levent Sagun, Utku Evci, V. Ugur Güney, Yann N. Dauphin, Léon Bottou

Proceedings of the 6th International Conference on Learning Representations, 2018

Hierarchical Neural Story Generation.

Angela Fan, Mike Lewis, Yann N. Dauphin

Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, 2018

2017

Tackling Over-pruning in Variational Autoencoders.

Serena Yeung, Anitha Kannan, Yann N. Dauphin, Li Fei-Fei

CoRR, 2017

Convolutional Sequence to Sequence Learning.

Jonas Gehring, Michael Auli, David Grangier, Denis Yarats, Yann N. Dauphin

Proceedings of the 34th International Conference on Machine Learning, 2017

Language Modeling with Gated Convolutional Networks.

Yann N. Dauphin, Angela Fan, Michael Auli, David Grangier

Proceedings of the 34th International Conference on Machine Learning, 2017

Parseval Networks: Improving Robustness to Adversarial Examples.

Moustapha Cissé, Piotr Bojanowski, Edouard Grave, Yann N. Dauphin, Nicolas Usunier

Proceedings of the 34th International Conference on Machine Learning, 2017

Deal or No Deal? End-to-End Learning of Negotiation Dialogues.

Mike Lewis, Denis Yarats, Yann N. Dauphin, Devi Parikh, Dhruv Batra

Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2017

A Convolutional Encoder Model for Neural Machine Translation.

Jonas Gehring, Michael Auli, David Grangier, Yann N. Dauphin

Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, 2017

2016

EmoNets: Multimodal deep learning approaches for emotion recognition in video.

Samira Ebrahimi Kahou, Xavier Bouthillier, Pascal Lamblin, Çaglar Gülçehre, Vincent Michalski, Kishore Konda, Sébastien Jean, Pierre Froumenty, Yann N. Dauphin, Nicolas Boulanger-Lewandowski, Raul Chandias Ferrari, Mehdi Mirza, David Warde-Farley, Aaron C. Courville, Pascal Vincent, Roland Memisevic, Christopher Joseph Pal, Yoshua Bengio

J. Multimodal User Interfaces, 2016

Predicting distributions with Linearizing Belief Networks.

Yann N. Dauphin, David Grangier

Proceedings of the 4th International Conference on Learning Representations, 2016

Theano: A Python framework for fast computation of mathematical expressions.

Rami Al-Rfou, Guillaume Alain, Amjad Almahairi, Christof Angermüller, Dzmitry Bahdanau, Nicolas Ballas, Frédéric Bastien, Justin Bayer, Anatoly Belikov, Alexander Belopolsky, Yoshua Bengio, Arnaud Bergeron, James Bergstra, Valentin Bisson, Josh Bleecher Snyder, Nicolas Bouchard, Nicolas Boulanger-Lewandowski, Xavier Bouthillier, Alexandre de Brébisson, Olivier Breuleux, Pierre Luc Carrier, Kyunghyun Cho, Jan Chorowski, Paul F. Christiano, Tim Cooijmans, Marc-Alexandre Côté, Myriam Côté, Aaron C. Courville, Yann N. Dauphin, Olivier Delalleau, Julien Demouth, Guillaume Desjardins, Sander Dieleman, Laurent Dinh, Melanie Ducoffe, Vincent Dumoulin, Samira Ebrahimi Kahou, Dumitru Erhan, Ziye Fan, Orhan Firat, Mathieu Germain, Xavier Glorot, Ian J. Goodfellow, Matthew Graham, Çaglar Gülçehre, Philippe Hamel, Iban Harlouchet, Jean-Philippe Heng, Balázs Hidasi, Sina Honari, Arjun Jain, Sébastien Jean, Kai Jia, Mikhail Korobov, Vivek Kulkarni, Alex Lamb, Pascal Lamblin, Eric Larsen, César Laurent, Sean Lee, Simon Lefrançois, Simon Lemieux, Nicholas Léonard, Zhouhan Lin, Jesse A. Livezey, Cory Lorenz, Jeremiah Lowin, Qianli Ma, Pierre-Antoine Manzagol, Olivier Mastropietro, Robert McGibbon, Roland Memisevic, Bart van Merriënboer, Vincent Michalski, Mehdi Mirza, Alberto Orlandi, Christopher Joseph Pal, Razvan Pascanu, Mohammad Pezeshki, Colin Raffel, Daniel Renshaw, Matthew Rocklin, Adriana Romero, Markus Roth, Peter Sadowski, John Salvatier, François Savard, Jan Schlüter, John Schulman, Gabriel Schwartz, Iulian Vlad Serban, Dmitriy Serdyuk, Samira Shabanian, Étienne Simon, Sigurd Spieckermann, S. Ramana Subramanyam, Jakub Sygnowski, Jérémie Tanguay, Gijs van Tulder, Joseph P. Turian, Sebastian Urban, Pascal Vincent, Francesco Visin, Harm de Vries, David Warde-Farley, Dustin J. Webb, Matthew Willson, Kelvin Xu, Lijun Xue, Li Yao, Saizheng Zhang, Ying Zhang

CoRR, 2016

2015

Using Recurrent Neural Networks for Slot Filling in Spoken Language Understanding.

Grégoire Mesnil, Yann N. Dauphin, Kaisheng Yao, Yoshua Bengio, Li Deng, Dilek Hakkani-Tür, Xiaodong He, Larry P. Heck, Gökhan Tür, Dong Yu, Geoffrey Zweig

IEEE ACM Trans. Audio Speech Lang. Process., 2015

RMSProp and equilibrated adaptive learning rates for non-convex optimization.

Yann N. Dauphin, Harm de Vries, Junyoung Chung, Yoshua Bengio

CoRR, 2015

Equilibrated adaptive learning rates for non-convex optimization.

Yann N. Dauphin, Harm de Vries, Yoshua Bengio

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2014

On the saddle point problem for non-convex optimization.

Razvan Pascanu, Yann N. Dauphin, Surya Ganguli, Yoshua Bengio

CoRR, 2014

Zero-Shot Learning and Clustering for Semantic Utterance Classification.

Yann N. Dauphin, Gökhan Tür, Dilek Hakkani-Tür, Larry P. Heck

Proceedings of the 2nd International Conference on Learning Representations, 2014

Identifying and attacking the saddle point problem in high-dimensional non-convex optimization.

Yann N. Dauphin, Razvan Pascanu, Çaglar Gülçehre, KyungHyun Cho, Surya Ganguli, Yoshua Bengio

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2013

Big Neural Networks Waste Capacity

Yann N. Dauphin, Yoshua Bengio

Proceedings of the 1st International Conference on Learning Representations, 2013

Stochastic Ratio Matching of RBMs for Sparse High-Dimensional Inputs.

Yann N. Dauphin, Yoshua Bengio

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Better Mixing via Deep Representations.

Yoshua Bengio, Grégoire Mesnil, Yann N. Dauphin, Salah Rifai

Proceedings of the 30th International Conference on Machine Learning, 2013

Combining modality specific deep neural networks for emotion recognition in video.

Samira Ebrahimi Kahou, Christopher J. Pal, Xavier Bouthillier, Pierre Froumenty, Çaglar Gülçehre, Roland Memisevic, Pascal Vincent, Aaron C. Courville, Yoshua Bengio, Raul Chandias Ferrari, Mehdi Mirza, Sébastien Jean, Pierre Luc Carrier, Yann N. Dauphin, Nicolas Boulanger-Lewandowski, Abhishek Aggarwal, Jeremie Zumer, Pascal Lamblin, Jean-Philippe Raymond, Guillaume Desjardins, Razvan Pascanu, David Warde-Farley, Atousa Torabi, Arjun Sharma, Emmanuel Bengio, Kishore Reddy Konda, Zhenzhou Wu

Proceedings of the 2013 International Conference on Multimodal Interaction, 2013

2012

Unsupervised and Transfer Learning Challenge: a Deep Learning Approach.

Grégoire Mesnil, Yann N. Dauphin, Xavier Glorot, Salah Rifai, Yoshua Bengio, Ian J. Goodfellow, Erick Lavoie, Xavier Muller, Guillaume Desjardins, David Warde-Farley, Pascal Vincent, Aaron C. Courville, James Bergstra

Proceedings of the Unsupervised and Transfer Learning, 2012

A Generative Process for Contractive Auto-Encoders.

Salah Rifai, Yann N. Dauphin, Pascal Vincent, Yoshua Bengio

Proceedings of the 29th International Conference on Machine Learning, 2012

2011

Higher Order Contractive Auto-Encoder.

Salah Rifai, Grégoire Mesnil, Pascal Vincent, Xavier Muller, Yoshua Bengio, Yann N. Dauphin, Xavier Glorot

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

The Manifold Tangent Classifier.

Salah Rifai, Yann N. Dauphin, Pascal Vincent, Yoshua Bengio, Xavier Muller

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Large-Scale Learning of Embeddings with Reconstruction Sampling.

Yann N. Dauphin, Xavier Glorot, Yoshua Bengio

Proceedings of the 28th International Conference on Machine Learning, 2011