Guillaume Rabusseau

Mila > À propos de Mila > Équipe > Guillaume Rabusseau
Membre Académique Principal
Guillaume Rabusseau
Professeur adjoint, Université de Montréal
Guillaume Rabusseau

Publications

2021-06

Lower and Upper Bounds on the VC-Dimension of Tensor Network Models.
Behnoush Khavari and Guillaume Rabusseau
arXiv preprint arXiv:2106.11827
(2021-06-22)
dblp.uni-trier.dePDF
Understanding Capacity Saturation in Incremental Learning
Shenyang Huang, Vincent Francois-Lavet and Guillaume Rabusseau
AI 2021
(2021-06-08)
caiac.pubpub.org
Extracting Weighted Automata for Approximate Minimization in Language Modelling.
arXiv preprint arXiv:2106.02965
(2021-06-05)
ui.adsabs.harvard.eduPDF

2021-03

Quantum Tensor Networks, Stochastic Processes, and Weighted Automata
Sandesh Adhikary, Siddarth Srinivasan, Jacob Miller, Guillaume Rabusseau and Byron Boots
AISTATS 2021
(2021-03-18)
proceedings.mlr.pressPDF
Tensor Networks for Probabilistic Sequence Modeling
Jacob Miller, Guillaume Rabusseau and John Terilla

2021-02

Optimal Spectral-Norm Approximate Minimization of Weighted Finite Automata
Borja Balle, Clara Lacroce, Prakash Panangaden, Doina Precup and Guillaume Rabusseau

2021-01

Horizontal gene transfer and recombination analysis of SARS-CoV-2 genes helps discover its close relatives and shed light on its origin.
Vladimir Makarenkov, Bogdan Mazoure, Guillaume Rabusseau and Pierre Legendre
Estimating the Impact of an Improvement to a Revenue Management System: An Airline Application.
arXiv: Learning
(2021-01-13)
dblp.uni-trier.dePDF
Assessing the Impact: Does an Improvement to a Revenue Management System Lead to an Improved Revenue?

2020-11

Approximate minimization of weighted tree automata
Borja Balle and Guillaume Rabusseau
Information & Computation
(2020-11-13)
www.sciencedirect.com

2020-10

Quantum Tensor Networks, Stochastic Processes, and Weighted Automata.
Siddarth Srinivasan, Sandesh Adhikary, Jacob Miller, Guillaume Rabusseau and Byron Boots
arXiv preprint arXiv:2010.10653
(2020-10-20)
ui.adsabs.harvard.eduPDF
Connecting Weighted Automata, Tensor Networks and Recurrent Neural Networks through Spectral Learning.
arXiv preprint arXiv:2010.10029
(2020-10-19)
dblp.uni-trier.dePDF

2020-08

Laplacian Change Point Detection for Dynamic Graphs
Shenyang Huang, Yasmeen Hitti, Guillaume Rabusseau and Reihaneh Rabbany
Adaptive Learning of Tensor Network Structures
Meraj Hashemizadeh, Michelle Liu, Jacob Miller and Guillaume Rabusseau
arXiv: Learning
(2020-08-12)
aps.arxiv.orgPDF
Adaptive Tensor Learning with Tensor Networks
Meraj Hashemizadeh, Michelle Liu, Jacob Miller and Guillaume Rabusseau
arXiv preprint arXiv:2008.05437
(2020-08-12)
ui.adsabs.harvard.eduPDF

2020-07

On Overfitting and Asymptotic Bias in Batch Reinforcement Learning with Partial Observability (Extended Abstract).
Vincent Francois-Lavet, Guillaume Rabusseau, Joelle Pineau, Damien Ernst and Raphael Fonteneau
IJCAI 2020
(2020-07-09)
www.ijcai.orgPDF

2020-06

Tensorized Random Projections
Beheshteh T. Rakhshan and Guillaume Rabusseau

2020-03

Tensor Networks for Language Modeling.
Jacob Miller, Guillaume Rabusseau and John Terilla
(venue unknown)
(2020-03-02)
dblp.uni-trier.dePDF
RandomNet: Towards Fully Automatic Neural Architecture Design for Multimodal Learning.
Stefano Alletto, Shenyang Huang, Vincent François-Lavet, Yohei Nakata and Guillaume Rabusseau
arXiv preprint arXiv:2003.01181
(2020-03-02)
ui.adsabs.harvard.eduPDF

2020-02

Representation of Reinforcement Learning Policies in Reproducing Kernel Hilbert Spaces.
Bogdan Mazoure, Thang Doan, Tianyu Li, Vladimir Makarenkov, Joelle Pineau, Doina Precup and Guillaume Rabusseau
arXiv preprint arXiv:2002.02863
(2020-02-07)
arxiv.orgPDF
Provably efficient reconstruction of policy networks.
Bogdan Mazoure, Thang Doan, Tianyu Li, Vladimir Makarenkov, Joelle Pineau, Doina Precup and Guillaume Rabusseau
arXiv: Learning
(2020-02-07)
ui.adsabs.harvard.eduPDF

2020-01

A Theoretical Analysis of Catastrophic Forgetting through the NTK Overlap Matrix.
Thang Doan, Mehdi Abbana Bennani, Bogdan Mazoure, Guillaume Rabusseau and Pierre Alquier

2019-11

Efficient Planning under Partial Observability with Unnormalized Q Functions and Spectral Learning
Tianyu Li, Bogdan Mazoure, Doina Precup and Guillaume Rabusseau

2019-09

Neural Architecture Search for Class-incremental Learning.
Shenyang Huang, Vincent François-Lavet and Guillaume Rabusseau
arXiv preprint arXiv:1909.06686
(2019-09-14)
ui.adsabs.harvard.eduPDF
Recognizable series on graphs and hypergraphs
Raphaël Bailly, Guillaume Rabusseau and François Denis
Journal of Computer and System Sciences
(2019-09-01)
www.sciencedirect.com

2019-05

On overfitting and asymptotic bias in batch reinforcement learning with partial observability
Vincent Francois-Lavet, Guillaume Rabusseau, Joelle Pineau, Damien Ernst and Raphael Fonteneau
Journal of Artificial Intelligence Research
(2019-05-05)
ui.adsabs.harvard.eduPDF

2018-12

Clustering-Oriented Representation Learning with Attractive-Repulsive Loss.
Kian Kenyon-Dean, Andre Cianflone, Lucas Page-Caccia, Guillaume Rabusseau, Jackie Chi Kit Cheung and Doina Precup
arXiv: Learning
(2018-12-18)
ui.adsabs.harvard.eduPDF

2018-10

Hierarchical Methods of Moments
Matteo Ruffini, Guillaume Rabusseau and Borja Balle
arXiv preprint arXiv:1810.07468
(2018-10-17)
arxiv.orgPDF

2018-07

Connecting Weighted Automata and Recurrent Neural Networks through Spectral Learning

2018-03

Nonlinear Weighted Finite Automata
AISTATS 2018
(2018-03-31)
dblp.uni-trier.dePDF

2018-02

Sequential Coordination of Deep Models for Learning Visual Arithmetic
arXiv preprint arXiv:1809.04988
(2018-02-15)
dblp.uni-trier.dePDF

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