biblio.bib

@preamble{{ \newcommand{\noop}[1]{} }}
@article{2RNN,
  title = {Connecting Weighted Automata and Recurrent Neural Networks through Spectral Learning},
  author = {Rabusseau, Guillaume and Li, Tianyu and Precup, Doina},
  journal = {arXiv preprint arXiv:1807.01406},
  year = {2018},
  arxiv = {https://arxiv.org/abs/1807.01406}
}
@article{crawford2018,
  title = {Sequential Coordination of Deep Models for Learning Visual Arithmetic},
  author = {Crawford, Eric and Rabusseau, Guillaume and Pineau, Joelle},
  year = {2018},
  pdf = {https://openreview.net/pdf?id=H1kMMmb0-}
}
@article{ICGI2018,
  title = {Learning Graph Weighted Models on Pictures},
  author = {Amortila, Philip and Rabusseau, Guillaume},
  journal = {ICGI},
  year = {2018},
  arxiv = {https://arxiv.org/abs/1806.08297}
}
@article{amortila2018,
  title = {Learning Graph Weighted Models on Pictures},
  author = {Amortila, Philip and Rabusseau, Guillaume},
  journal = {2nd workshop on Learning and Automata (LearnAut at FLoC 2018)},
  year = {2018}
}
@incollection{AISTATS2018,
  title = {Nonlinear Weighted Finite Automata},
  author = {Li, Tianyu and Rabusseau, Guillaume and Precup, Doina},
  booktitle = {International Conference on Artificial Intelligence and Statistics},
  pages = {679--688},
  year = {2018},
  pdf = {http://proceedings.mlr.press/v84/li18a}
}
@incollection{FOSSACS2018,
  title = {Minimization of Graph Weighted Models over Circular Strings},
  author = {Rabusseau, Guillaume},
  booktitle = {International Conference on Foundations of Software Science and Computation Structures},
  pages = {513--529},
  year = {2018},
  organization = {Springer},
  pdf = {https://link.springer.com/chapter/10.1007/978-3-319-89366-2_28}
}
@article{JCSS2018,
  author = {Bailly, Rapha{\"e}l and Rabusseau, Guillaume and Fran{\c{c}}ois Denis},
  year = {2018 (in press)},
  title = {Recognizable Series on Graphs and Hypergraphs},
  journal = {Journal of Computer and System Sciences},
  preprint = {./files/JCSS2017.pdf},
  pdf = {http://www.sciencedirect.com/science/article/pii/S0022000017301563}
}
@incollection{NIPS17-a,
  title = {Multitask Spectral Learning of Weighted Automata},
  author = {Rabusseau, Guillaume and Balle, Borja and Pineau, Joelle},
  booktitle = {Advances in Neural Information Processing Systems 30},
  pages = {2585--2594},
  year = {2017},
  pdf = {http://papers.nips.cc/paper/6852-multitask-spectral-learning-of-weighted-automata}
}
@incollection{NIPS17-b,
  title = {Hierarchical Methods of Moments},
  author = {Ruffini, Matteo and Rabusseau, Guillaume and Balle, Borja},
  booktitle = {Advances in Neural Information Processing Systems 30},
  pages = {1899--1908},
  year = {2017},
  pdf = {http://papers.nips.cc/paper/6786-hierarchical-methods-of-moments}
}
@article{NIPS16-ws,
  title = {Graph Learning as a Tensor Factorization Problem},
  author = {Bailly, Rapha{\"e}l and Rabusseau, Guillaume},
  journal = {NIPS workshop on Learning with Tensors},
  year = {2016},
  pdf = {https://hal.archives-ouvertes.fr/hal-01519851/}
}
@article{LICS17-ws1,
  title = {Multitask Spectral Learning of Weighted Automata},
  author = {Rabusseau, Guillaume and Pineau, Joelle},
  journal = {LICS workshop on Learning and Automata},
  year = {2017}
}
@article{LICS17-ws2,
  title = {Neural Network Based Nonlinear Weighted Finite Automata},
  author = {Li, Tianyu and Rabusseau, Guillaume and Precup, Doina},
  journal = {LICS workshop on Learning and Automata},
  year = {2017}
}
@phdthesis{rabusseau2016thesis,
  title = {A Tensor Perspective on Weighted Automata, Low-Rank Regression
  and Algebraic Mixtures},
  author = {Guillaume Rabusseau},
  year = {2016},
  school = {Aix-Marseille Université},
  pdf = {./files/phd_rabusseau_final.pdf}
}
@incollection{NIPS16,
  title = {Low-Rank Regression with Tensor Responses},
  author = {Rabusseau, Guillaume and Kadri, Hachem},
  booktitle = {Advances In Neural Information Processing Systems 29},
  pages = {1867--1875},
  year = {2016},
  pdf = {./files/nips2016.pdf},
  poster = {./files/nips2016-poster.pdf},
  code = {https://github.com/grwip/HOLRR}
}
@inproceedings{AISTATS16,
  title = {{Low-Rank Approximation of Weighted Tree Automata}},
  author = {Rabusseau, Guillaume and Balle, Borja and Cohen, Shay B.},
  booktitle = {Proceedings of the 19th International Conference on Artificial Intelligence and Statistics},
  pages = {839--847},
  year = {2016},
  arxiv = {http://arxiv.org/abs/1511.01442},
  pdf = {http://proceedings.mlr.press/v51/rabusseau16.html},
  poster = {./files/AISTATS16-poster.pdf}
}
@article{CAP16-a,
  author = {Guillaume Rabusseau},
  title = {{Régression de faible rang pour réponses tensorielles}},
  journal = {Conférence sur l'Apprentissage Automatique},
  locdate = {Marseille, France, July 5-7},
  year = {2016}
}
@article{CAP16-b,
  author = {Guillaume Rabusseau and Borja Balle and Shay B. Cohen},
  title = {{Minimisation approximée d'automates pondérés d'arbres}},
  journal = {Conférence sur l'Apprentissage Automatique},
  locdate = {Marseille, France, July 5-7},
  year = {2016}
}
@inproceedings{LATA15,
  author = {Rapha{\"{e}}l Bailly and
               Fran{\c{c}}ois Denis and
               Guillaume Rabusseau},
  title = {{Recognizable Series on Hypergraphs}},
  booktitle = {Proceedings of the 9th International
               Conference on Language and Automata Theory and Applications},
  locdate = {Nice, France, March 2-6, 2015},
  pages = {639--651},
  year = {2015},
  slides = {./files/LATA2015-slides.pdf},
  arxiv = {http://arxiv.org/abs/1404.7533}
}
@article{GRETSI15,
  author = {Guillaume Rabusseau and Hachem Kadri and
               Fran{\c{c}}ois Denis},
  title = {{Régression de faible rang non-paramétrique pour réponses tensorielles}},
  journal = {Colloque International Francophone de Traitement du Signal et de l'Image},
  locdate = {Lyon, France, September 8-11},
  year = {2015},
  no_poster = {./files/GRETSI15-poster.pdf}
}
@inproceedings{ICGI14,
  author = {Guillaume Rabusseau and
               Fran{\c{c}}ois Denis},
  title = {{Maximizing a Tree Series in the Representation Space}},
  booktitle = {Proceedings of the 12th International Conference on Grammatical Inference},
  locdate = {Kyoto, Japan, September 17-19, 2014},
  pages = {124--138},
  year = {2014},
  pdf = {http://jmlr.csail.mit.edu/proceedings/papers/v34/rabusseau14a.pdf},
  slides = {./files/ICGI2014-slides.pdf}
}
@article{rabusseau2014learning,
  author = {Guillaume Rabusseau and
               Fran{\c{c}}ois Denis},
  title = {{Learning Negative Mixture Models by Tensor Decompositions}},
  journal = {CoRR},
  volume = {abs/1403.4224},
  year = {2014},
  arxiv = {http://arxiv.org/abs/1403.4224}
}
@article{CAP14,
  author = {Guillaume Rabusseau and
               Fran{\c{c}}ois Denis},
  title = {{Décompositions Tensorielles pour l'Apprentissage de Modèles de Mélanges Négatifs}},
  journal = {Conférence sur l'Apprentissage Automatique},
  locdate = {Saint-Etienne, France, July 4-7},
  year = {2014},
  note = {\textbf{Best  paper award}},
  slides = {./files/CAP2014-slides.pdf}
}
@article{ICMLworkshop14,
  author = {Guillaume Rabusseau and
               Fran{\c{c}}ois Denis},
  title = {{Learning Negative Mixture Models by Tensor Decompositions}},
  journal = {Workshop on Method of Moments and Spectral Learning (ICML 2014)},
  locdate = {Beijing, China, June 25},
  year = {2014},
  poster = {./files/ICMLworkshop14-poster.pdf}
}

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