| Beyond Local Nash Equilibria for Adversarial Networks FA Oliehoek, R Savani, J Gallego-Posada, E Pol, R Groß Benelux Conference on Artificial Intelligence, 73-89, 2018 | 43 | 2018 |
| GANGs: Generative Adversarial Network Games FA Oliehoek, R Savani, J Gallego-Posada, E Van der Pol, ED De Jong, ... arXiv preprint arXiv:1712.00679, 2017 | 43 | 2017 |
| Detection and Diagnosis of Breast Tumors using Deep Convolutional Neural Networks J Gallego-Posada, DA Montoya-Zapata, OL Quintero-Montoya Latin American Conference in Automatic Control, 11-17, 2016 | 37 | 2016 |
| Controlled Sparsity via Constrained Optimization or: How I Learned to Stop Tuning Penalties and Love Constraints J Gallego-Posada, J Ramirez, A Erraqabi, Y Bengio, S Lacoste-Julien NeurIPS2022 - 36th Conference on Neural Information Processing Systems, 2022 | 14 | 2022 |
| Equivariant Mesh Attention Networks S Basu, J Gallego-Posada, F Viganò, J Rowbottom, T Cohen TMLR - Transactions on Machine Learning Research, 2022 | 11 | 2022 |
| Cooper: a toolkit for Lagrangian-based constrained optimization J Gallego-Posada, J Ramirez | 8 | 2022 |
| Interval Analysis and Optimization Applied to Parameter Estimation under Uncertainty J Gallego-Posada, M Puerta-Yepes Boletim da Sociedade Paranaense de Matemática 36 (2), 107-124, 2018 | 8 | 2018 |
| A distributed data-parallel pytorch implementation of the distributed shampoo optimizer for training neural networks at-scale HJM Shi, TH Lee, S Iwasaki, J Gallego-Posada, Z Li, K Rangadurai, ... arXiv preprint arXiv:2309.06497, 2023 | 5 | 2023 |
| How to make your optimizer generalize better S Vaswani, R Babanezhad, J Gallego-Posada, A Mishkin, ... 12th OPT Workshop on Optimization for Machine Learning @ NeurIPS2020, 2020 | 5* | 2020 |
| Lonie: Compressing COINs with L-constraints J Ramirez, J Gallego-Posada Sparsity in Neural Networks Workshop, 2022 | 4 | 2022 |
| Simplicial Regularization J Gallego-Posada, P Forré Workshop on Geometrical and Topological Representation Learning @ ICLR2021, 2021 | 3 | 2021 |
| GAIT: A Geometric Approach to Information Theory J Gallego-Posada, A Vani, M Schwarzer, S Lacoste-Julien AISTATS2020 - Proceedings of the 23rd International Conference on Artificial …, 2020 | 3* | 2020 |
| Flexible Learning of Sparse Neural Networks via Constrained Regularization J Gallego-Posada, J Ramirez De Los Rios, A Erraqabi NeurIPS 2021 LatinX in AI Workshop, 2021 | 2 | 2021 |
| Balancing Act: Sparse Models with Constrained Disparate Impact M Hashemizadeh, J Ramirez, R Sukumaran, G Farnadi, S Lacoste-Julien, ... ICLR2024, 2023 | 1* | 2023 |
| Data Analytics Applications in Latin America and Emerging Economies E Rodriguez CRC Press, 2017 | 1 | 2017 |
| On PI controllers for updating Lagrange multipliers in constrained optimization M Sohrabi, J Ramirez, TH Zhang, S Lacoste-Julien, J Gallego-Posada arXiv preprint arXiv:2406.04558, 2024 | | 2024 |
| Simplicial AutoEncoders: A connection between Algebraic Topology and Probabilistic Modelling J Gallego-Posada University of Amsterdam, 2018 | | 2018 |
| GAIT: A Geometric Approach to Information Theory= GAIT: Un Enfoque Geométrico a la Teoría de la Información J Gallego Posada, A Vani, M Schwarzer, S Lacoste Julien | | |
| Analysis of high dimensional distributions with decoupled norm and direction J Gallego-Posada, A Vani, M Schwarzer, S Lotfi | | |
Simon Lacoste-JulienAssociate Professor - Canada CIFAR AI Chair, University of Montreal / MilaVerified email at iro.umontreal.ca
