| Low-Rank Regression with Tensor Responses G Rabusseau, H Kadri Advances in Neural Information Processing Systems, 1867-1875, 2016 | 21 | 2016 |
| A Tensor Perspective on Weighted Automata, Low-Rank Regression and Algebraic Mixtures G Rabusseau Aix-Marseille Université, 2016 | 7 | 2016 |
| Recognizable series on hypergraphs R Bailly, F Denis, G Rabusseau International Conference on Language and Automata Theory and Applications …, 2015 | 6 | 2015 |
| Tensor regression networks with various low-rank tensor approximations X Cao, G Rabusseau arXiv preprint arXiv:1712.09520, 2017 | 5 | 2017 |
| Connecting weighted automata and recurrent neural networks through spectral learning G Rabusseau, T Li, D Precup arXiv preprint arXiv:1807.01406, 2018 | 4 | 2018 |
| Multitask spectral learning of weighted automata G Rabusseau, B Balle, J Pineau Advances in Neural Information Processing Systems, 2588-2597, 2017 | 4 | 2017 |
| Low-rank approximation of weighted tree automata G Rabusseau, B Balle, S Cohen Artificial Intelligence and Statistics, 839-847, 2016 | 4 | 2016 |
| Recognizable series on graphs and hypergraphs R Bailly, G Rabusseau, F Denis Journal of Computer and System Sciences 104, 58-81, 2019 | 3 | 2019 |
| On overfitting and asymptotic bias in batch reinforcement learning with partial observability V François-Lavet, G Rabusseau, J Pineau, D Ernst, R Fonteneau Journal of Artificial Intelligence Research 65, 1-30, 2019 | 3 | 2019 |
| Clustering-Oriented Representation Learning with Attractive-Repulsive Loss K Kenyon-Dean, A Cianflone, L Page-Caccia, G Rabusseau, ... arXiv preprint arXiv:1812.07627, 2018 | 3 | 2018 |
| Nonlinear Weighted Finite Automata T Li, G Rabusseau, D Precup International Conference on Artificial Intelligence and Statistics, 679-688, 2018 | 3* | 2018 |
| Optimizing Home Energy Management and Electric Vehicle Charging with Reinforcement Learning RG Di Wu, F lavet Vincent, P Doina, B Benoit Proceedings of the 16th Adaptive Learning Agents, 2018 | 2 | 2018 |
| Learning negative mixture models by tensor decompositions G Rabusseau, F Denis arXiv preprint arXiv:1403.4224, 2014 | 2 | 2014 |
| Minimization of Graph Weighted Models over Circular Strings G Rabusseau International Conference on Foundations of Software Science and Computation …, 2018 | 1 | 2018 |
| Hierarchical methods of moments M Ruffini, G Rabusseau, B Balle Advances in Neural Information Processing Systems, 1901-1911, 2017 | 1 | 2017 |
| Efficient Planning under Partial Observability with Unnormalized Q Functions and Spectral Learning T Li, B Mazoure, D Precup, G Rabusseau arXiv preprint arXiv:1911.05010, 2019 | | 2019 |
| Approximate Minimization of Weighted Tree Automata B Balle, G Rabusseau | | 2019 |
| Neural Architecture Search for Class-incremental Learning S Huang, V François-Lavet, G Rabusseau arXiv preprint arXiv:1909.06686, 2019 | | 2019 |
| Proceedings of the Workshop on Deep Learning and Formal Languages: Building Bridges J Eisner, M Gallé, J Heinz, A Quattoni, G Rabusseau Proceedings of the Workshop on Deep Learning and Formal Languages: Building …, 2019 | | 2019 |
| Sequential Coordination of Deep Models for Learning Visual Arithmetic E Crawford, G Rabusseau, J Pineau arXiv preprint arXiv:1809.04988, 2018 | | 2018 |
Doina PrecupDeepMind and McGill UniversityEmail verificata su cs.mcgill.ca
