← Authors

Romain Couillet

25 papers · 2016–2025 · 7 conferences · across top CS/AI conferences

Achievements

🌍 Conference Polyglot (7) πŸƒ Academic Marathon (9) 🐝 Cross-Pollinator (8) 🐣 Hot Topic Early Bird πŸ—ΊοΈ Taxonomy Completionist (14) πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🌈 Renaissance Researcher (7) πŸ‘‘ Triple Crown 🧬 Topic Evolution πŸ† Keyword Champion (4) πŸ”₯ Unstoppable (6) πŸ’Ž Century Club (25) πŸ—ƒοΈ Keyword Collector (90) ⚑ Prolific Year (5)

Conferences

ICML (8) JMLR (6) ICLR (4) NIPS (3) AISTATS (2) CONLL (1) EMNLP (1)

Top co-authors

Hafiz Tiomoko Ali (5) Zhenyu Liao (5) Florent Chatelain (3) Nicolas Tremblay (3) Mohamed Tamaazousti (3) Lorenzo Dall'Amico (3) Malik Tiomoko (3) Mohamed El Amine Seddik (3) Eric Gaussier (2) Hugo Lebeau (2)

Keywords

random matrix theory (9) random matrix (8) spectral clustering (7) gaussian mixture model (5) community detection (5) spectral analysis (4) graph theory (4) kernel matrix (3) word embedding (2) principal component analysis (2) high dimensional datum (2) multi-task learning (2) natural language processing (2) asymptotic analysis (2) semi-supervised learning (2) representation learning (2) network analysis (2) tensor decomposition (2) stochastic block model (2) echo state network (2)

Papers

A Random Matrix Approach to Low-Multilinear-Rank Tensor Approximation JMLR 2025
PCA-based Multi-Task Learning: a Random Matrix Approach ICML 2023
Asymptotic Bayes risk of semi-supervised multitask learning on Gaussian mixture AISTATS 2023
A Random Matrix Perspective on Random Tensors JMLR 2022
Random matrices in service of ML footprint: ternary random features with no performance loss ICLR 2022
A Random Matrix Analysis of Data Stream Clustering: Coping With Limited Memory Resources ICML 2022
Two-way kernel matrix puncturing: towards resource-efficient PCA and spectral clustering ICML 2021
Consistent Semi-Supervised Graph Regularization for High Dimensional Data JMLR 2021
The Unexpected Deterministic and Universal Behavior of Large Softmax Classifiers AISTATS 2021
Deciphering and Optimizing Multi-Task Learning: a Random Matrix Approach ICLR 2021
Sparse Quantized Spectral Clustering ICLR 2021
A Unified Framework for Spectral Clustering in Sparse Graphs JMLR 2021
Word Representations Concentrate and This is Good News! EMNLP 2020
Word Representations Concentrate and This is Good News! CONLL 2020
A random matrix analysis of random Fourier features: beyond the Gaussian kernel, a precise phase transition, and the corresponding double descent NIPS 2020
Random Matrix Theory Proves that Deep Learning Representations of GAN-data Behave as Gaussian Mixtures ICML 2020
Community detection in sparse time-evolving graphs with a dynamical Bethe-Hessian NIPS 2020
Revisiting the Bethe-Hessian: Improved Community Detection in Sparse Heterogeneous Graphs NIPS 2019
A Kernel Random Matrix-Based Approach for Sparse PCA ICLR 2019
Random Matrix Improved Covariance Estimation for a Large Class of Metrics ICML 2019
Improved spectral community detection in large heterogeneous networks JMLR 2018
The Dynamics of Learning: A Random Matrix Approach ICML 2018
On the Spectrum of Random Features Maps of High Dimensional Data ICML 2018
The Asymptotic Performance of Linear Echo State Neural Networks JMLR 2016
A Random Matrix Approach to Echo-State Neural Networks ICML 2016