Guillaume Rabusseau
Guillaume Rabusseau
Assistant Professor - Université de Montréal / Mila
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Low-Rank Regression with Tensor Responses
G Rabusseau, H Kadri
Advances in Neural Information Processing Systems, 1867-1875, 2016
A Tensor Perspective on Weighted Automata, Low-Rank Regression and Algebraic Mixtures
G Rabusseau
Aix-Marseille Université, 2016
Recognizable series on hypergraphs
R Bailly, F Denis, G Rabusseau
International Conference on Language and Automata Theory and Applications …, 2015
Low-rank approximation of weighted tree automata
G Rabusseau, B Balle, S Cohen
Artificial Intelligence and Statistics, 839-847, 2016
Tensor regression networks with various low-rank tensor approximations
X Cao, G Rabusseau
arXiv preprint arXiv:1712.09520, 2017
Recognizable series on graphs and hypergraphs
R Bailly, G Rabusseau, F Denis
Journal of Computer and System Sciences, 2017
Multitask spectral learning of weighted automata
G Rabusseau, B Balle, J Pineau
Advances in Neural Information Processing Systems, 2588-2597, 2017
Minimization of Graph Weighted Models over Circular Strings
G Rabusseau
International Conference on Foundations of Software Science and Computation …, 2018
Nonlinear Weighted Finite Automata
T Li, G Rabusseau, D Precup
International Conference on Artificial Intelligence and Statistics, 679-688, 2018
Hierarchical methods of moments
M Ruffini, G Rabusseau, B Balle
Advances in Neural Information Processing Systems, 1901-1911, 2017
Learning negative mixture models by tensor decompositions
G Rabusseau, F Denis
arXiv preprint arXiv:1403.4224, 2014
Clustering-Oriented Representation Learning with Attractive-Repulsive Loss
K Kenyon-Dean, A Cianflone, L Page-Caccia, G Rabusseau, ...
arXiv preprint arXiv:1812.07627, 2018
Sequential Coordination of Deep Models for Learning Visual Arithmetic
E Crawford, G Rabusseau, J Pineau
arXiv preprint arXiv:1809.04988, 2018
Connecting Weighted Automata and Recurrent Neural Networks through Spectral Learning
G Rabusseau, T Li, D Precup
arXiv preprint arXiv:1807.01406, 2018
Learning Graph Weighted Models on Pictures
P Amortila, G Rabusseau
2nd workshop on Learning and Automata (LearnAut at FLoC 2018), 2018
Graph Learning as a Tensor Factorization Problem
R Bailly, G Rabusseau
NIPS 2017 workshop on Learning with Tensors, 2017
Maximizing a Tree Series in the Representation Space.
G Rabusseau, F Denis
ICGI, 124-138, 2014
Approche du langage de Conlon Nancarrow: Méthode de composition et structure de l'étude# 2a pour piano mécanique
G Rabusseau
Optimizing Home Energy Management and Electric Vehicle Charging with Reinforcement Learning
D Wu, G Rabusseau, V François-lavet, D Precup, B Boulet
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Artikelen 1–19