Couillet, Romain

23 publications

JMLR 2025 A Random Matrix Approach to Low-Multilinear-Rank Tensor Approximation Hugo Lebeau, Florent Chatelain, Romain Couillet

AISTATS 2023 Asymptotic Bayes Risk of Semi-Supervised Multitask Learning on Gaussian Mixture Minh-Toan Nguyen, Romain Couillet

ICML 2023 PCA-Based Multi-Task Learning: A Random Matrix Approach Malik Tiomoko, Romain Couillet, Frederic Pascal

ICML 2022 A Random Matrix Analysis of Data Stream Clustering: Coping with Limited Memory Resources Hugo Lebeau, Romain Couillet, Florent Chatelain

JMLR 2022 A Random Matrix Perspective on Random Tensors José Henrique de M. Goulart, Romain Couillet, Pierre Comon

ICLR 2022 Random Matrices in Service of ML Footprint: Ternary Random Features with No Performance Loss Hafiz Tiomoko Ali, Zhenyu Liao, Romain Couillet

AISTATS 2021 The Unexpected Deterministic and Universal Behavior of Large SoftMax Classifiers Mohamed El Amine Seddik, Cosme Louart, Romain Couillet, Mohamed Tamaazousti

JMLR 2021 A Unified Framework for Spectral Clustering in Sparse Graphs Lorenzo Dall'Amico, Romain Couillet, Nicolas Tremblay

JMLR 2021 Consistent Semi-Supervised Graph Regularization for High Dimensional Data Xiaoyi Mai, Romain Couillet

ICLR 2021 Deciphering and Optimizing Multi-Task Learning: A Random Matrix Approach Malik Tiomoko, Hafiz Tiomoko Ali, Romain Couillet

ICLR 2021 Sparse Quantized Spectral Clustering Zhenyu Liao, Romain Couillet, Michael W. Mahoney

ICML 2021 Two-Way Kernel Matrix Puncturing: Towards Resource-Efficient PCA and Spectral Clustering Romain Couillet, Florent Chatelain, Nicolas Le Bihan

ICMLW 2020 A Random Matrix Analysis of Learning with Α-Dropout Mohamed El Amine Seddik, Romain Couillet, Mohamed Tamaazousti

NeurIPS 2020 A Random Matrix Analysis of Random Fourier Features: Beyond the Gaussian Kernel, a Precise Phase Transition, and the Corresponding Double Descent Zhenyu Liao, Romain Couillet, Michael W. Mahoney

NeurIPS 2020 Community Detection in Sparse Time-Evolving Graphs with a Dynamical Bethe-Hessian Lorenzo Dall'Amico, Romain Couillet, Nicolas Tremblay

ICML 2020 Random Matrix Theory Proves That Deep Learning Representations of GAN-Data Behave as Gaussian Mixtures Mohamed El Amine Seddik, Cosme Louart, Mohamed Tamaazousti, Romain Couillet

ICLR 2019 A Kernel Random Matrix-Based Approach for Sparse PCA Mohamed El Amine Seddik, Mohamed Tamaazousti, Romain Couillet

ICML 2019 Random Matrix Improved Covariance Estimation for a Large Class of Metrics Malik Tiomoko, Romain Couillet, Florent Bouchard, Guillaume Ginolhac

NeurIPS 2019 Revisiting the Bethe-Hessian: Improved Community Detection in Sparse Heterogeneous Graphs Lorenzo Dall'Amico, Romain Couillet, Nicolas Tremblay

ICML 2018 On the Spectrum of Random Features Maps of High Dimensional Data Zhenyu Liao, Romain Couillet

ICML 2018 The Dynamics of Learning: A Random Matrix Approach Zhenyu Liao, Romain Couillet

ICML 2016 A Random Matrix Approach to Echo-State Neural Networks Romain Couillet, Gilles Wainrib, Hafiz Tiomoko Ali, Harry Sevi

JMLR 2016 The Asymptotic Performance of Linear Echo State Neural Networks Romain Couillet, Gilles Wainrib, Harry Sevi, Hafiz Tiomoko Ali