| Fairness-aware structured pruning in transformers A Zayed, G Mordido, S Shabanian, I Baldini, S Chandar Proceedings of the AAAI Conference on Artificial Intelligence 38 (20), 22484 …, 2024 | 4 | 2024 |
| Successor Features for Efficient Multisubject Controlled Text Generation M Cao, M Fatemi, JCK Cheung, S Shabanian arXiv preprint arXiv:2311.04921, 2023 | | 2023 |
| Deep learning on a healthy data diet: Finding important examples for fairness A Zayed, P Parthasarathi, G Mordido, H Palangi, S Shabanian, S Chandar Proceedings of the AAAI Conference on Artificial Intelligence 37 (12), 14593 …, 2023 | 13 | 2023 |
| Should we attend more or less? modulating attention for fairness A Zayed, G Mordido, S Shabanian, S Chandar arXiv preprint arXiv:2305.13088, 2023 | 8 | 2023 |
| Systematic rectification of language models via dead-end analysis M Cao, M Fatemi, JCK Cheung, S Shabanian arXiv preprint arXiv:2302.14003, 2023 | 9 | 2023 |
| Benchmarking bias mitigation algorithms in representation learning through fairness metrics C Reddy | 30 | 2022 |
| Learning to limit data collection via scaling laws: A computational interpretation for the legal principle of data minimization D Shanmugam, F Diaz, S Shabanian, M Finck, A Biega Proceedings of the 2022 ACM Conference on Fairness, Accountability, and …, 2022 | 16 | 2022 |
| Learning to Limit Data Collection via Scaling Laws: Supplementary Material D Shanmugam, F Diaz, S Shabanian, M Finck, AJ Biega | | 2022 |
| Learning to limit data collection via scaling laws: Data minimization compliance in practice D Shanmugam, S Shabanian, F Diaz, M Finck, A Biega ACM FAccT, 2022 | 3 | 2022 |
| Convexity and boundedness relaxation for fixed point theorems in modular spaces F Lael, S Shabanian Applied General Topology 22 (1), 91-108, 2021 | 2 | 2021 |
| On the learning dynamics of deep neural networks R Tachet, M Pezeshki, S Shabanian, A Courville, Y Bengio arXiv preprint arXiv:1809.06848, 2018 | 33 | 2018 |
| Convergence properties of deep neural networks on separable data RT des Combes, M Pezeshki, S Shabanian, A Courville, Y Bengio | 2 | 2018 |
| On the learning dynamics of deep neural networks RT Combes, M Pezeshki, S Shabanian, A Courville, Y Bengio arXiv preprint arXiv:1809.06848, 2018 | 7 | 2018 |
| Variational bi-lstms S Shabanian, D Arpit, A Trischler, Y Bengio arXiv preprint arXiv:1711.05717, 2017 | 41 | 2017 |
| Bidirectional Helmholtz Machines S Shabanian | | 2016 |
| The KKM theorem in modular spaces and applications to minimax inequalities S Shabanian, SM Vaezpour Bulletin of the Malaysian Mathematical Sciences Society 39, 921-931, 2016 | 6 | 2016 |
| Bidirectional helmholtz machines J Bornschein, S Shabanian, A Fischer, Y Bengio International Conference on Machine Learning, 2511-2519, 2016 | 29 | 2016 |
| Theano: A Python framework for fast computation of mathematical expressions TTD Team, R Al-Rfou, G Alain, A Almahairi, C Angermueller, D Bahdanau, ... arXiv preprint arXiv:1605.02688, 2016 | 214 | 2016 |
| Harm de Vries, David Warde-Farley, Dustin J R Al-Rfou, G Alain, A Almahairi, C Angermueller, D Bahdanau, N Ballas, ... Webb, Matthew Willson, Kelvin Xu, Lijun Xue, Li Yao, Saizheng Zhang, and …, 2016 | 30 | 2016 |
| 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 | 920 | 2016 |
Yoshua BengioProfessor of computer science, University of Montreal, Mila, IVADO, CIFARVerified email at umontreal.ca