Yann N. Dauphin

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 51

Top Topics

Convex Optimization

Story Generation

Mathematical Expressions

Top Venues

Publications

Vincent Dumoulin, Daniel D. Johnson, Pablo Samuel Castro, Hugo Larochelle, Yann N. Dauphin
A density estimation perspective on learning from pairwise human preferences. Trans. Mach. Learn. Res. 2024 (2024)
Yann N. Dauphin, Atish Agarwala, Hossein Mobahi
Neglected Hessian component explains mysteries in Sharpness regularization. CoRR (2024)
Atish Agarwala, Yann N. Dauphin
SAM operates far from home: eigenvalue regularization as a dynamical phenomenon. CoRR (2023)
Emirhan Kurtulus, Zichao Li, Yann N. Dauphin, Ekin Dogus Cubuk
Tied-Augment: Controlling Representation Similarity Improves Data Augmentation. ICML (2023)
Alina Beygelzimer, Yann N. Dauphin, Percy Liang, Jennifer Wortman Vaughan
Has the Machine Learning Review Process Become More Arbitrary as the Field Has Grown? The NeurIPS 2021 Consistency Experiment. CoRR (2023)
Atish Agarwala, Yann N. Dauphin
SAM operates far from home: eigenvalue regularization as a dynamical phenomenon. ICML (2023)
Vincent Dumoulin, Daniel D. Johnson, Pablo Samuel Castro, Hugo Larochelle, Yann N. Dauphin
A density estimation perspective on learning from pairwise human preferences. CoRR (2023)
Atish Agarwala, Samuel Stern Schoenholz, Jeffrey Pennington, Yann N. Dauphin
Temperature check: theory and practice for training models with softmax-cross-entropy losses. Trans. Mach. Learn. Res. 2023 (2023)
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
JaxPruner: A concise library for sparsity research. CoRR (2023)
Emirhan Kurtulus, Zichao Li, Yann N. Dauphin, Ekin Dogus Cubuk
Tied-Augment: Controlling Representation Similarity Improves Data Augmentation. CoRR (2023)
Charvi Rastogi, Ivan Stelmakh, Alina Beygelzimer, Yann N. Dauphin, Percy Liang, Jennifer Wortman Vaughan, Zhenyu Xue, Hal Daumé III, Emma Pierson, Nihar B. Shah
How do Authors' Perceptions of their Papers Compare with Co-authors' Perceptions and Peer-review Decisions? CoRR (2022)
Utku Evci, Yani Ioannou, Cem Keskin, Yann N. Dauphin
Gradient Flow in Sparse Neural Networks and How Lottery Tickets Win. AAAI (2022)
Wojciech Sirko, Sergii Kashubin, Marvin Ritter, Abigail Annkah, Yasser Salah Eddine Bouchareb, Yann N. Dauphin, Daniel Keysers, Maxim Neumann, Moustapha Cissé, John Quinn
Continental-Scale Building Detection from High Resolution Satellite Imagery. CoRR (2021)
Lucio M. Dery, Yann N. Dauphin, David Grangier
Auxiliary Task Update Decomposition: The Good, The Bad and The Neutral. CoRR (2021)
Lucio M. Dery, Yann N. Dauphin, David Grangier
Auxiliary Task Update Decomposition: the Good, the Bad and the neutral. ICLR (2021)
Jiaming Song, Lunjia Hu, Yann N. Dauphin, Michael Auli, Tengyu Ma
Robust and On-the-fly Dataset Denoising for Image Classification. CoRR (2020)
Atish Agarwala, Jeffrey Pennington, Yann N. Dauphin, Samuel S. Schoenholz
Temperature check: theory and practice for training models with softmax-cross-entropy losses. CoRR (2020)
Jiaming Song, Yann N. Dauphin, Michael Auli, Tengyu Ma
Robust and On-the-Fly Dataset Denoising for Image Classification. ECCV (29) (2020)
Utku Evci, Yani Andrew Ioannou, Cem Keskin, Yann N. Dauphin
Gradient Flow in Sparse Neural Networks and How Lottery Tickets Win. CoRR (2020)
Kyra Yee, Yann N. Dauphin, Michael Auli
Simple and Effective Noisy Channel Modeling for Neural Machine Translation. EMNLP/IJCNLP (1) (2019)
Sara Hooker, Aaron C. Courville, Yann N. Dauphin, Andrea Frome
Selective Brain Damage: Measuring the Disparate Impact of Model Pruning. CoRR (2019)
Angela Fan, Mike Lewis, Yann N. Dauphin
Strategies for Structuring Story Generation. CoRR (2019)
Angela Fan, Mike Lewis, Yann N. Dauphin
Strategies for Structuring Story Generation. ACL (1) (2019)
Ryan Lowe, Jakob N. Foerster, Y-Lan Boureau, Joelle Pineau, Yann N. Dauphin
On the Pitfalls of Measuring Emergent Communication. CoRR (2019)
Felix Wu, Angela Fan, Alexei Baevski, Yann N. Dauphin, Michael Auli
Pay Less Attention with Lightweight and Dynamic Convolutions. ICLR (2019)
Kyra Yee, Nathan Ng, Yann N. Dauphin, Michael Auli
Simple and Effective Noisy Channel Modeling for Neural Machine Translation. CoRR (2019)
Ryan Lowe, Jakob N. Foerster, Y-Lan Boureau, Joelle Pineau, Yann N. Dauphin
On the Pitfalls of Measuring Emergent Communication. AAMAS (2019)
Yann N. Dauphin, Samuel S. Schoenholz
MetaInit: Initializing learning by learning to initialize. NeurIPS (2019)
Hongyi Zhang, Yann N. Dauphin, Tengyu Ma
Fixup Initialization: Residual Learning Without Normalization. CoRR (2019)
Felix Wu, Angela Fan, Alexei Baevski, Yann N. Dauphin, Michael Auli
Pay Less Attention with Lightweight and Dynamic Convolutions. CoRR (2019)
Hongyi Zhang, Yann N. Dauphin, Tengyu Ma
Fixup Initialization: Residual Learning Without Normalization. ICLR (Poster) (2019)
Levent Sagun, Utku Evci, V. Ugur Güney, Yann N. Dauphin, Léon Bottou
Empirical Analysis of the Hessian of Over-Parametrized Neural Networks. ICLR (Workshop) (2018)
Hongyi Zhang, Moustapha Cissé, Yann N. Dauphin, David Lopez-Paz
mixup: Beyond Empirical Risk Minimization. ICLR (Poster) (2018)
Angela Fan, Mike Lewis, Yann N. Dauphin
Hierarchical Neural Story Generation. CoRR (2018)
Angela Fan, Mike Lewis, Yann N. Dauphin
Hierarchical Neural Story Generation. ACL (1) (2018)
Jonas Gehring, Michael Auli, David Grangier, Yann N. Dauphin
A Convolutional Encoder Model for Neural Machine Translation. ACL (1) (2017)
Jonas Gehring, Michael Auli, David Grangier, Denis Yarats, Yann N. Dauphin
Convolutional Sequence to Sequence Learning. CoRR (2017)
Jonas Gehring, Michael Auli, David Grangier, Denis Yarats, Yann N. Dauphin
Convolutional Sequence to Sequence Learning. ICML (2017)
Moustapha Cissé, Piotr Bojanowski, Edouard Grave, Yann N. Dauphin, Nicolas Usunier
Parseval Networks: Improving Robustness to Adversarial Examples. ICML (2017)
Mike Lewis, Denis Yarats, Yann N. Dauphin, Devi Parikh, Dhruv Batra
Deal or No Deal? End-to-End Learning of Negotiation Dialogues. EMNLP (2017)
Serena Yeung, Anitha Kannan, Yann N. Dauphin, Li Fei-Fei
Tackling Over-pruning in Variational Autoencoders. CoRR (2017)
Moustapha Cissé, Piotr Bojanowski, Edouard Grave, Yann N. Dauphin, Nicolas Usunier
Parseval Networks: Improving Robustness to Adversarial Examples. CoRR (2017)
Yann N. Dauphin, Angela Fan, Michael Auli, David Grangier
Language Modeling with Gated Convolutional Networks. ICML (2017)
Mike Lewis, Denis Yarats, Yann N. Dauphin, Devi Parikh, Dhruv Batra
Deal or No Deal? End-to-End Learning for Negotiation Dialogues. CoRR (2017)
Levent Sagun, Utku Evci, V. Ugur Güney, Yann N. Dauphin, Léon Bottou
Empirical Analysis of the Hessian of Over-Parametrized Neural Networks. CoRR (2017)
Hongyi Zhang, Moustapha Cissé, Yann N. Dauphin, David Lopez-Paz
mixup: Beyond Empirical Risk Minimization. CoRR (2017)
Yann N. Dauphin, David Grangier
Predicting distributions with Linearizing Belief Networks. ICLR (Poster) (2016)
Yann N. Dauphin, Angela Fan, Michael Auli, David Grangier
Language Modeling with Gated Convolutional Networks. CoRR (2016)
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
Theano: A Python framework for fast computation of mathematical expressions. CoRR (2016)
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
EmoNets: Multimodal deep learning approaches for emotion recognition in video. J. Multimodal User Interfaces 10 (2) (2016)
Jonas Gehring, Michael Auli, David Grangier, Yann N. Dauphin
A Convolutional Encoder Model for Neural Machine Translation. CoRR (2016)
Yann N. Dauphin, Harm de Vries, Junyoung Chung, Yoshua Bengio
RMSProp and equilibrated adaptive learning rates for non-convex optimization. CoRR (2015)
Yann N. Dauphin, Harm de Vries, Yoshua Bengio
Equilibrated adaptive learning rates for non-convex optimization. NIPS (2015)
Samira Ebrahimi Kahou, Xavier Bouthillier, Pascal Lamblin, Çaglar Gülçehre, Vincent Michalski, Kishore Reddy 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 J. Pal, Yoshua Bengio
EmoNets: Multimodal deep learning approaches for emotion recognition in video. CoRR (2015)
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
Using Recurrent Neural Networks for Slot Filling in Spoken Language Understanding. IEEE ACM Trans. Audio Speech Lang. Process. 23 (3) (2015)
Yann N. Dauphin, Gökhan Tür, Dilek Hakkani-Tür, Larry P. Heck
Zero-Shot Learning and Clustering for Semantic Utterance Classification. ICLR (Poster) (2014)
Razvan Pascanu, Yann N. Dauphin, Surya Ganguli, Yoshua Bengio
On the saddle point problem for non-convex optimization. CoRR (2014)
Yann N. Dauphin, Razvan Pascanu, Çaglar Gülçehre, KyungHyun Cho, Surya Ganguli, Yoshua Bengio
Identifying and attacking the saddle point problem in high-dimensional non-convex optimization. NIPS (2014)
Yann N. Dauphin, Razvan Pascanu, Çaglar Gülçehre, Kyunghyun Cho, Surya Ganguli, Yoshua Bengio
Identifying and attacking the saddle point problem in high-dimensional non-convex optimization. CoRR (2014)
Yann N. Dauphin, Yoshua Bengio
Stochastic Ratio Matching of RBMs for Sparse High-Dimensional Inputs. NIPS (2013)
Yoshua Bengio, Grégoire Mesnil, Yann N. Dauphin, Salah Rifai
Better Mixing via Deep Representations. ICML (1) (2013)
Yann N. Dauphin, Yoshua Bengio
Big Neural Networks Waste Capacity ICLR (Workshop) (2013)
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
Combining modality specific deep neural networks for emotion recognition in video. ICMI (2013)
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
Unsupervised and Transfer Learning Challenge: a Deep Learning Approach. ICML Unsupervised and Transfer Learning (2012)
Salah Rifai, Yann N. Dauphin, Pascal Vincent, Yoshua Bengio
A Generative Process for Contractive Auto-Encoders. ICML (2012)
Yoshua Bengio, Grégoire Mesnil, Yann N. Dauphin, Salah Rifai
Better Mixing via Deep Representations CoRR (2012)
Yann N. Dauphin, Xavier Glorot, Yoshua Bengio
Large-Scale Learning of Embeddings with Reconstruction Sampling. ICML (2011)
Salah Rifai, Grégoire Mesnil, Pascal Vincent, Xavier Muller, Yoshua Bengio, Yann N. Dauphin, Xavier Glorot
Higher Order Contractive Auto-Encoder. ECML/PKDD (2) (2011)
Salah Rifai, Yann N. Dauphin, Pascal Vincent, Yoshua Bengio, Xavier Muller
The Manifold Tangent Classifier. NIPS (2011)