Guillaume Rabusseau
Guillaume Rabusseau
Assistant Professor - Canada CIFAR AI Chair, Université de Montréal / Mila
Verified email at iro.umontreal.ca - Homepage
Title
Cited by
Cited by
Year
Low-Rank Regression with Tensor Responses
G Rabusseau, H Kadri
Advances in Neural Information Processing Systems, 1867-1875, 2016
37*2016
A Tensor Perspective on Weighted Automata, Low-Rank Regression and Algebraic Mixtures
G Rabusseau
Aix-Marseille Université, 2016
112016
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
102019
Connecting weighted automata and recurrent neural networks through spectral learning
G Rabusseau, T Li, D Precup
arXiv preprint arXiv:1807.01406, 2018
102018
Tensor regression networks with various low-rank tensor approximations
X Cao, G Rabusseau
arXiv preprint arXiv:1712.09520, 2017
102017
Recognizable series on hypergraphs
R Bailly, F Denis, G Rabusseau
International Conference on Language and Automata Theory and Applications …, 2015
92015
Multitask spectral learning of weighted automata
G Rabusseau, B Balle, J Pineau
Advances in Neural Information Processing Systems, 2588-2597, 2017
72017
Clustering-oriented representation learning with attractive-repulsive loss
K Kenyon-Dean, A Cianflone, L Page-Caccia, G Rabusseau, ...
arXiv preprint arXiv:1812.07627, 2018
52018
Nonlinear Weighted Finite Automata
T Li, G Rabusseau, D Precup
International Conference on Artificial Intelligence and Statistics, 679-688, 2018
5*2018
Recognizable series on graphs and hypergraphs
R Bailly, G Rabusseau, F Denis
Journal of Computer and System Sciences 104, 58-81, 2019
42019
Low-rank approximation of weighted tree automata
G Rabusseau, B Balle, S Cohen
Artificial Intelligence and Statistics, 839-847, 2016
42016
Tensorized Random Projections
BT Rakhshan, G Rabusseau
arXiv preprint arXiv:2003.05101, 2020
32020
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
32018
Neural Architecture Search for Class-incremental Learning
S Huang, V François-Lavet, G Rabusseau
arXiv preprint arXiv:1909.06686, 2019
22019
Minimization of Graph Weighted Models over Circular Strings
G Rabusseau
International Conference on Foundations of Software Science and Computation …, 2018
22018
Hierarchical methods of moments
M Ruffini, G Rabusseau, B Balle
Advances in Neural Information Processing Systems, 1901-1911, 2017
22017
Learning negative mixture models by tensor decompositions
G Rabusseau, F Denis
arXiv preprint arXiv:1403.4224, 2014
22014
Adaptive Tensor Learning with Tensor Networks
M Hashemizadeh, M Liu, J Miller, G Rabusseau
arXiv preprint arXiv:2008.05437, 2020
12020
Tensor Networks for Probabilistic Sequence Modeling
J Miller, G Rabusseau, J Terilla
arXiv preprint arXiv:2003.01039, 2020
1*2020
Provably efficient reconstruction of policy networks
B Mazoure, T Doan, T Li, V Makarenkov, J Pineau, D Precup, ...
arXiv preprint arXiv:2002.02863, 2020
12020
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