| Learning Representations and Generative Models for 3D Point Clouds P Achlioptas, O Diamanti, I Mitliagkas, L Guibas International Conference on Machine Learning, 2018 | 1957 | 2018 |
| Manifold mixup: Better representations by interpolating hidden states V Verma, A Lamb, C Beckham, A Najafi, I Mitliagkas, A Courville, ... arXiv preprint arXiv:1806.05236, 2018 | 1836 | 2018 |
| Manifold mixup: Better representations by interpolating hidden states V Verma, A Lamb, C Beckham, A Najafi, I Mitliagkas, A Courville, ... arXiv preprint arXiv:1806.05236, 2018 | 1836 | 2018 |
| Invariance principle meets information bottleneck for out-of-distribution generalization K Ahuja, E Caballero, D Zhang, JC Gagnon-Audet, Y Bengio, I Mitliagkas, ... Advances in Neural Information Processing Systems 34, 3438-3450, 2021 | 403 | 2021 |
| Gotta go fast when generating data with score-based models A Jolicoeur-Martineau, K Li, R Piché-Taillefer, T Kachman, I Mitliagkas arXiv preprint arXiv:2105.14080, 2021 | 305 | 2021 |
| A modern take on the bias-variance tradeoff in neural networks B Neal, S Mittal, A Baratin, V Tantia, M Scicluna, S Lacoste-Julien, ... arXiv preprint arXiv:1810.08591, 2018 | 262 | 2018 |
| Generalizing to unseen domains via distribution matching I Albuquerque, J Monteiro, M Darvishi, TH Falk, I Mitliagkas arXiv preprint arXiv:1911.00804, 2019 | 254* | 2019 |
| Negative momentum for improved game dynamics G Gidel, RA Hemmat, M Pezeshki, G Huang, R Lepriol, S Lacoste-Julien, ... Artificial Intelligence and Statistics, 2019 | 229 | 2019 |
| Memory limited, streaming PCA I Mitliagkas, C Caramanis, P Jain Advances in neural information processing systems 26, 2013 | 207 | 2013 |
| Asynchrony begets momentum, with an application to deep learning I Mitliagkas, C Zhang, S Hadjis, C Ré 2016 54th Annual Allerton Conference on Communication, Control, and …, 2016 | 180 | 2016 |
| Adversarial score matching and improved sampling for image generation A Jolicoeur-Martineau, R Piché-Taillefer, RT Combes, I Mitliagkas arXiv preprint arXiv:2009.05475, 2020 | 158 | 2020 |
| In search of robust measures of generalization GK Dziugaite, A Drouin, B Neal, N Rajkumar, E Caballero, L Wang, ... Advances in Neural Information Processing Systems 33, 11723-11733, 2020 | 135 | 2020 |
| Parallel SGD: When does averaging help? J Zhang, C De Sa, I Mitliagkas, C Ré arXiv preprint arXiv:1606.07365, 2016 | 134 | 2016 |
| A tight and unified analysis of gradient-based methods for a whole spectrum of differentiable games W Azizian, I Mitliagkas, S Lacoste-Julien, G Gidel International conference on artificial intelligence and statistics, 2863-2873, 2020 | 128 | 2020 |
| Yellowfin and the art of momentum tuning J Zhang, I Mitliagkas SysML, 2019 | 126 | 2019 |
| Accelerated stochastic power iteration P Xu, B He, C De Sa, I Mitliagkas, C Re International Conference on Artificial Intelligence and Statistics, 58-67, 2018 | 117 | 2018 |
| Representation learning and adversarial generation of 3D point clouds P Achlioptas, O Diamanti, I Mitliagkas, L Guibas arXiv preprint arXiv:1707.02392, 2017 | 106 | 2017 |
| Deep learning at 15pf: supervised and semi-supervised classification for scientific data T Kurth, J Zhang, N Satish, E Racah, I Mitliagkas, MMA Patwary, T Malas, ... Proceedings of the International Conference for High Performance Computing …, 2017 | 96 | 2017 |
| Multi-objective training of Generative Adversarial Networks with multiple discriminators I Albuquerque, J Monteiro, T Doan, B Considine, T Falk, I Mitliagkas International Conference on Machine Learning, 2019 | 95 | 2019 |
| Joint power and admission control for ad-hoc and cognitive underlay networks: Convex approximation and distributed implementation I Mitliagkas, ND Sidiropoulos, A Swami IEEE Transactions on Wireless Communications 10 (12), 4110-4121, 2011 | 92 | 2011 |
Yoshua BengioProfessor of computer science, University of Montreal, Mila, IVADO, CIFARVerified email at umontreal.ca
