Aladin Virmaux

According to our database, Aladin Virmaux authored at least 11 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Unlocking the Potential of Transformers in Time Series Forecasting with Sharpness-Aware Minimization and Channel-Wise Attention.

Romain Ilbert, Ambroise Odonnat, Vasilii Feofanov, Aladin Virmaux, Giuseppe Paolo, Themis Palpanas, Ievgen Redko

CoRR, 2024

2023

Random Matrix Analysis to Balance between Supervised and Unsupervised Learning under the Low Density Separation Assumption.

Vasilii Feofanov, Malik Tiomoko, Aladin Virmaux

Proceedings of the International Conference on Machine Learning, 2023

2022

Deciphering Lasso-based Classification Through a Large Dimensional Analysis of the Iterative Soft-Thresholding Algorithm.

Malik Tiomoko, Ekkehard Schnoor, Mohamed El Amine Seddik, Igor Colin, Aladin Virmaux

Proceedings of the International Conference on Machine Learning, 2022

2021

Knothe-Rosenblatt transport for Unsupervised Domain Adaptation.

Aladin Virmaux, Illyyne Saffar, Jianfeng Zhang, Balázs Kégl

CoRR, 2021

Improving Hierarchical Adversarial Robustness of Deep Neural Networks.

Avery Ma, Aladin Virmaux, Kevin Scaman, Juwei Lu

CoRR, 2021

Lipschitz normalization for self-attention layers with application to graph neural networks.

George Dasoulas, Kevin Scaman, Aladin Virmaux

Proceedings of the 38th International Conference on Machine Learning, 2021

Ego-Based Entropy Measures for Structural Representations on Graphs.

George Dasoulas, Giannis Nikolentzos, Kevin Scaman, Aladin Virmaux, Michalis Vazirgiannis

Proceedings of the IEEE International Conference on Acoustics, 2021

2020

Ego-based Entropy Measures for Structural Representations.

George Dasoulas, Giannis Nikolentzos, Kevin Scaman, Aladin Virmaux, Michalis Vazirgiannis

CoRR, 2020

Coloring Graph Neural Networks for Node Disambiguation.

George Dasoulas, Ludovic Dos Santos, Kevin Scaman, Aladin Virmaux

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

2018

Lipschitz regularity of deep neural networks: analysis and efficient estimation.

Aladin Virmaux, Kevin Scaman

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2016

Théorie des représentations combinatoire de tours de monoïdes : Application à la catégorification et aux fonctions de parking. (Combinatorial representation theory of tower monoids : Application to categorification and to parking functions).

Aladin Virmaux

PhD thesis, 2016