Guillaume Rabusseau

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 73

Top Topics

Finite Automata

Reinforcement Learning

Top Venues

Publications

Julia Gastinger, Shenyang Huang, Mikhail Galkin, Erfan Loghmani, Ali Parviz, Farimah Poursafaei, Jacob Danovitch, Emanuele Rossi, Ioannis Koutis, Heiner Stuckenschmidt, Reihaneh Rabbany, Guillaume Rabusseau
TGB 2.0: A Benchmark for Learning on Temporal Knowledge Graphs and Heterogeneous Graphs. CoRR (2024)
Vivek Bharadwaj, Beheshteh T. Rakhshan, Osman Asif Malik, Guillaume Rabusseau
Efficient Leverage Score Sampling for Tensor Train Decomposition. CoRR (2024)
Volodimir Mitarchuk, Clara Lacroce, Rémi Eyraud, Rémi Emonet, Amaury Habrard, Guillaume Rabusseau
Length independent PAC-Bayes bounds for Simple RNNs. AISTATS (2024)
Marawan Gamal Abdel Hameed, Aristides Milios, Siva Reddy, Guillaume Rabusseau
ROSA: Random Subspace Adaptation for Efficient Fine-Tuning. CoRR (2024)
Shenyang Huang, Farimah Poursafaei, Reihaneh Rabbany, Guillaume Rabusseau, Emanuele Rossi
UTG: Towards a Unified View of Snapshot and Event Based Models for Temporal Graphs. CoRR (2024)
Dominique Beaini, Shenyang Huang, Joao Alex Cunha, Zhiyi Li, Gabriela Moisescu-Pareja, Oleksandr Dymov, Samuel Maddrell-Mander, Callum McLean, Frederik Wenkel, Luis Müller, Jama Hussein Mohamud, Ali Parviz, Michael Craig, Michal Koziarski, Jiarui Lu, Zhaocheng Zhu, Cristian Gabellini, Kerstin Klaser, Josef Dean, Cas Wognum, Maciej Sypetkowski, Guillaume Rabusseau, Reihaneh Rabbany, Jian Tang, Christopher Morris, Mirco Ravanelli, Guy Wolf, Prudencio Tossou, Hadrien Mary, Therence Bois, Andrew W. Fitzgibbon, Blazej Banaszewski, Chad Martin, Dominic Masters
Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets. ICLR (2024)
Shenyang Huang, Samy Coulombe, Yasmeen Hitti, Reihaneh Rabbany, Guillaume Rabusseau
Laplacian Change Point Detection for Single and Multi-view Dynamic Graphs. ACM Trans. Knowl. Discov. Data 18 (3) (2024)
Maude Lizaire, Michael Rizvi-Martel, Marawan Gamal Abdel Hameed, Guillaume Rabusseau
A Tensor Decomposition Perspective on Second-order RNNs. CoRR (2024)
Razieh Shirzadkhani, Tran Gia Bao Ngo, Kiarash Shamsi, Shenyang Huang, Farimah Poursafaei, Poupak Azad, Reihaneh Rabbany, Baris Coskunuzer, Guillaume Rabusseau, Cuneyt Gurcan Akcora
Towards Neural Scaling Laws for Foundation Models on Temporal Graphs. CoRR (2024)
Michael Rizvi, Maude Lizaire, Clara Lacroce, Guillaume Rabusseau
Simulating Weighted Automata over Sequences and Trees with Transformers. CoRR (2024)
Michael Rizvi-Martel, Maude Lizaire, Clara Lacroce, Guillaume Rabusseau
Simulating weighted automata over sequences and trees with transformers. AISTATS (2024)
Tianyu Li, Doina Precup, Guillaume Rabusseau
Connecting weighted automata, tensor networks and recurrent neural networks through spectral learning. Mach. Learn. 113 (5) (2024)
Clara Lacroce, Borja Balle, Prakash Panangaden, Guillaume Rabusseau
Optimal Approximate Minimization of One-Letter Weighted Finite Automata. CoRR (2023)
Shenyang Huang, Jacob Danovitch, Guillaume Rabusseau, Reihaneh Rabbany
Fast and Attributed Change Detection on Dynamic Graphs with Density of States. CoRR (2023)
Shenyang Huang, Samy Coulombe, Yasmeen Hitti, Reihaneh Rabbany, Guillaume Rabusseau
Laplacian Change Point Detection for Single and Multi-view Dynamic Graphs. CoRR (2023)
Alex Meiburg, Jing Chen, Jacob Miller, Raphaëlle Tihon, Guillaume Rabusseau, Alejandro Perdomo-Ortiz
Generative Learning of Continuous Data by Tensor Networks. CoRR (2023)
Shenyang Huang, Jacob Danovitch, Guillaume Rabusseau, Reihaneh Rabbany
Fast and Attributed Change Detection on Dynamic Graphs with Density of States. PAKDD (1) (2023)
Farzaneh Heidari, Perouz Taslakian, Guillaume Rabusseau
Explaining Graph Neural Networks Using Interpretable Local Surrogates. TAG-ML (2023)
Dominique Beaini, Shenyang Huang, Joao Alex Cunha, Zhiyi Li, Gabriela Moisescu-Pareja, Oleksandr Dymov, Samuel Maddrell-Mander, Callum McLean, Frederik Wenkel, Luis Müller, Jama Hussein Mohamud, Ali Parviz, Michael Craig, Michal Koziarski, Jiarui Lu, Zhaocheng Zhu, Cristian Gabellini, Kerstin Klaser, Josef Dean, Cas Wognum, Maciej Sypetkowski, Guillaume Rabusseau, Reihaneh Rabbany, Jian Tang, Christopher Morris, Ioannis Koutis, Mirco Ravanelli, Guy Wolf, Prudencio Tossou, Hadrien Mary, Therence Bois, Andrew W. Fitzgibbon, Blazej Banaszewski, Chad Martin, Dominic Masters
Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets. CoRR (2023)
Shenyang Huang, Farimah Poursafaei, Jacob Danovitch, Matthias Fey, Weihua Hu, Emanuele Rossi, Jure Leskovec, Michael M. Bronstein, Guillaume Rabusseau, Reihaneh Rabbany
Temporal Graph Benchmark for Machine Learning on Temporal Graphs. CoRR (2023)
Shenyang Huang, Farimah Poursafaei, Jacob Danovitch, Matthias Fey, Weihua Hu, Emanuele Rossi, Jure Leskovec, Michael M. Bronstein, Guillaume Rabusseau, Reihaneh Rabbany
Temporal Graph Benchmark for Machine Learning on Temporal Graphs. NeurIPS (2023)
Kaiwen Hou, Guillaume Rabusseau
Spectral Regularization: an Inductive Bias for Sequence Modeling. CoRR (2022)
Borja Balle, Guillaume Rabusseau
Approximate minimization of weighted tree automata. Inf. Comput. 282 (2022)
Chenqing Hua, Guillaume Rabusseau, Jian Tang
High-Order Pooling for Graph Neural Networks with Tensor Decomposition. NeurIPS (2022)
Clara Lacroce, Prakash Panangaden, Guillaume Rabusseau
Towards an AAK Theory Approach to Approximate Minimization in the Multi-Letter Case. CoRR (2022)
Bogdan Mazoure, Thang Doan, Tianyu Li, Vladimir Makarenkov, Joelle Pineau, Doina Precup, Guillaume Rabusseau
Low-Rank Representation of Reinforcement Learning Policies. J. Artif. Intell. Res. 75 (2022)
Tianyu Li, Bogdan Mazoure, Guillaume Rabusseau
Sequential Density Estimation via NCWFAs Sequential Density Estimation via Nonlinear Continuous Weighted Finite Automata. CoRR (2022)
Chenqing Hua, Guillaume Rabusseau, Jian Tang
High-Order Pooling for Graph Neural Networks with Tensor Decomposition. CoRR (2022)
Clara Lacroce, Prakash Panangaden, Guillaume Rabusseau
Extracting Weighted Automata for Approximate Minimization in Language Modelling. CoRR (2021)
Borja Balle, Clara Lacroce, Prakash Panangaden, Doina Precup, Guillaume Rabusseau
Optimal Spectral-Norm Approximate Minimization of Weighted Finite Automata. ICALP (2021)
Thang Doan, Mehdi Abbana Bennani, Bogdan Mazoure, Guillaume Rabusseau, Pierre Alquier
A Theoretical Analysis of Catastrophic Forgetting through the NTK Overlap Matrix. AISTATS (2021)
Behnoush Khavari, Guillaume Rabusseau
Lower and Upper Bounds on the Pseudo-Dimension of Tensor Network Models. NeurIPS (2021)
Behnoush Khavari, Guillaume Rabusseau
Lower and Upper Bounds on the VC-Dimension of Tensor Network Models. CoRR (2021)
Borja Balle, Clara Lacroce, Prakash Panangaden, Doina Precup, Guillaume Rabusseau
Optimal Spectral-Norm Approximate Minimization of Weighted Finite Automata. CoRR (2021)
Clara Lacroce, Prakash Panangaden, Guillaume Rabusseau
Extracting Weighted Automata for Approximate Minimization in Language Modelling. ICGI (2021)
Beheshteh T. Rakhshan, Guillaume Rabusseau
Rademacher Random Projections with Tensor Networks. CoRR (2021)
Jacob Miller, Guillaume Rabusseau, John Terilla
Tensor Networks for Probabilistic Sequence Modeling. AISTATS (2021)
Greta Laage, Emma Frejinger, William L. Hamilton, Andrea Lodi, Guillaume Rabusseau
Estimating the Impact of an Improvement to a Revenue Management System: An Airline Application. CoRR (2021)
Shenyang Huang, Vincent François-Lavet, Guillaume Rabusseau
Understanding Capacity Saturation in Incremental Learning. Canadian Conference on AI (2021)
Sandesh Adhikary, Siddarth Srinivasan, Jacob Miller, Guillaume Rabusseau, Byron Boots
Quantum Tensor Networks, Stochastic Processes, and Weighted Automata. AISTATS (2021)
Beheshteh T. Rakhshan, Guillaume Rabusseau
Tensorized Random Projections. CoRR (2020)
Shenyang Huang, Yasmeen Hitti, Guillaume Rabusseau, Reihaneh Rabbany
Laplacian Change Point Detection for Dynamic Graphs. KDD (2020)
Tianyu Li, Doina Precup, Guillaume Rabusseau
Connecting Weighted Automata, Tensor Networks and Recurrent Neural Networks through Spectral Learning. CoRR (2020)
Thang Doan, Mehdi Abbana Bennani, Bogdan Mazoure, Guillaume Rabusseau, Pierre Alquier
A Theoretical Analysis of Catastrophic Forgetting through the NTK Overlap Matrix. CoRR (2020)
Shenyang Huang, Yasmeen Hitti, Guillaume Rabusseau, Reihaneh Rabbany
Laplacian Change Point Detection for Dynamic Graphs. CoRR (2020)
Meraj Hashemizadeh, Michelle Liu, Jacob Miller, Guillaume Rabusseau
Adaptive Tensor Learning with Tensor Networks. CoRR (2020)
Tianyu Li, Bogdan Mazoure, Doina Precup, Guillaume Rabusseau
Efficient Planning under Partial Observability with Unnormalized Q Functions and Spectral Learning. AISTATS (2020)
Vincent François-Lavet, Guillaume Rabusseau, Joelle Pineau, Damien Ernst, Raphael Fonteneau
On Overfitting and Asymptotic Bias in Batch Reinforcement Learning with Partial Observability (Extended Abstract). IJCAI (2020)
Siddarth Srinivasan, Sandesh Adhikary, Jacob Miller, Guillaume Rabusseau, Byron Boots
Quantum Tensor Networks, Stochastic Processes, and Weighted Automata. CoRR (2020)
Stefano Alletto, Shenyang Huang, Vincent François-Lavet, Yohei Nakata, Guillaume Rabusseau
RandomNet: Towards Fully Automatic Neural Architecture Design for Multimodal Learning. CoRR (2020)
Jacob Miller, Guillaume Rabusseau, John Terilla
Tensor Networks for Language Modeling. CoRR (2020)
Beheshteh T. Rakhshan, Guillaume Rabusseau
Tensorized Random Projections. AISTATS (2020)
Bogdan Mazoure, Thang Doan, Tianyu Li, Vladimir Makarenkov, Joelle Pineau, Doina Precup, Guillaume Rabusseau
Provably efficient reconstruction of policy networks. CoRR (2020)
Raphaël Bailly, Guillaume Rabusseau, François Denis
Recognizable series on graphs and hypergraphs. J. Comput. Syst. Sci. 104 (2019)
Tianyu Li, Bogdan Mazoure, Doina Precup, Guillaume Rabusseau
Efficient Planning under Partial Observability with Unnormalized Q Functions and Spectral Learning. CoRR (2019)
Guillaume Rabusseau, Tianyu Li, Doina Precup
Connecting Weighted Automata and Recurrent Neural Networks through Spectral Learning. AISTATS (2019)
Vincent François-Lavet, Guillaume Rabusseau, Joelle Pineau, Damien Ernst, Raphael Fonteneau
On Overfitting and Asymptotic Bias in Batch Reinforcement Learning with Partial Observability. J. Artif. Intell. Res. 65 (2019)
Shenyang Huang, Vincent François-Lavet, Guillaume Rabusseau
Neural Architecture Search for Class-incremental Learning. CoRR (2019)
Philip Amortila, Guillaume Rabusseau
Learning Graph Weighted Models on Pictures. ICGI (2018)
Matteo Ruffini, Guillaume Rabusseau, Borja Balle
Hierarchical Methods of Moments. CoRR (2018)
Guillaume Rabusseau
Minimization of Graph Weighted Models over Circular Strings. FoSSaCS (2018)
Philip Amortila, Guillaume Rabusseau
Learning Graph Weighted Models on Pictures. CoRR (2018)
Eric Crawford, Guillaume Rabusseau, Joelle Pineau
Sequential Coordination of Deep Models for Learning Visual Arithmetic. CoRR (2018)
Guillaume Rabusseau, Tianyu Li, Doina Precup
Connecting Weighted Automata and Recurrent Neural Networks through Spectral Learning. CoRR (2018)
Tianyu Li, Guillaume Rabusseau, Doina Precup
Nonlinear Weighted Finite Automata. AISTATS (2018)
Kian Kenyon-Dean, Andre Cianflone, Lucas Page-Caccia, Guillaume Rabusseau, Jackie Chi Kit Cheung, Doina Precup
Clustering-Oriented Representation Learning with Attractive-Repulsive Loss. CoRR (2018)
Xingwei Cao, Guillaume Rabusseau, Joelle Pineau
Tensor Regression Networks with various Low-Rank Tensor Approximations. CoRR (2017)
Guillaume Rabusseau, Borja Balle, Joelle Pineau
Multitask Spectral Learning of Weighted Automata. NIPS (2017)
Tianyu Li, Guillaume Rabusseau, Doina Precup
Neural Network Based Nonlinear Weighted Finite Automata. CoRR (2017)
Matteo Ruffini, Guillaume Rabusseau, Borja Balle
Hierarchical Methods of Moments. NIPS (2017)
Guillaume Rabusseau, Borja Balle, Shay B. Cohen
Low-Rank Approximation of Weighted Tree Automata. AISTATS (2016)
Guillaume Rabusseau, Hachem Kadri
Higher-Order Low-Rank Regression. CoRR (2016)
Guillaume Rabusseau, Hachem Kadri
Low-Rank Regression with Tensor Responses. NIPS (2016)
Guillaume Rabusseau, Borja Balle, Shay B. Cohen
Weighted Tree Automata Approximation by Singular Value Truncation. CoRR (2015)
Raphaël Bailly, François Denis, Guillaume Rabusseau
Recognizable Series on Hypergraphs. LATA (2015)
Raphaël Bailly, François Denis, Guillaume Rabusseau
Recognizable Series on Hypergraphs. CoRR (2014)
Guillaume Rabusseau, François Denis
Maximizing a Tree Series in the Representation Space. ICGI (2014)
Guillaume Rabusseau, François Denis
Learning Negative Mixture Models by Tensor Decompositions. CoRR (2014)