Mohamed El Amine Seddik

According to our database, Mohamed El Amine Seddik authored at least 22 papers between 2018 and 2024.

Collaborative distances:

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

2024

Performance Gaps in Multi-view Clustering under the Nested Matrix-Tensor Model.

Hugo Lebeau, Mohamed El Amine Seddik, José Henrique de Morais Goulart

CoRR, 2024

Do Vision and Language Encoders Represent the World Similarly?

Mayug Maniparambil, Raiymbek Akshulakov, Yasser Abdelaziz Dahou Djilali, Sanath Narayan, Mohamed El Amine Seddik, Karttikeya Mangalam, Noel E. O'Connor

CoRR, 2024

2023

A Nested Matrix-Tensor Model for Noisy Multi-view Clustering.

Mohamed El Amine Seddik, Mastane Achab, Henrique Goulart, Mérouane Debbah

CoRR, 2023

Hotelling Deflation on Large Symmetric Spiked Tensors.

Mohamed El Amine Seddik, José Henrique de Morais Goulart, Maxime Guillaud

CoRR, 2023

Learning from Low Rank Tensor Data: A Random Tensor Theory Perspective.

Mohamed El Amine Seddik, Malik Tiomoko, Alexis Decurninge, Maxim Panov, Maxime Guillaud

Proceedings of the Uncertainty in Artificial Intelligence, 2023

On the Accuracy of Hotelling-Type Asymmetric Tensor Deflation: A Random Tensor Analysis.

Mohamed El Amine Seddik, Maxime Guillaud, Alexis Decurninge, José Henrique de Morais Goulart

Proceedings of the 9th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2023

2022

Soil Moisture Estimation Using Sentinel-1/-2 Imagery Coupled With CycleGAN for Time-Series Gap Filing.

Natalia Efremova, Mohamed El Amine Seddik, Esra Erten

IEEE Trans. Geosci. Remote. Sens., 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

Node Feature Kernels Increase Graph Convolutional Network Robustness.

Mohamed El Amine Seddik, Changmin Wu, Johannes F. Lutzeyer, Michalis Vazirgiannis

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Neural Networks Classify through the Class-Wise Means of Their Representations.

Mohamed El Amine Seddik, Mohamed Tamaazousti

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Deep Miner: A Deep and Multi-branch Network which Mines Rich and Diverse Features for Person Re-identification.

Abdallah Benzine, Mohamed El Amine Seddik, Julien Desmarais

CoRR, 2021

Optimization-Based Neural Networks Compression.

Younes Tahiri, Mohamed El Amine Seddik, Mohamed Tamaazousti

Proceedings of the 2021 IEEE International Conference on Image Processing, 2021

The Unexpected Deterministic and Universal Behavior of Large Softmax Classifiers.

Mohamed El Amine Seddik, Cosme Louart, Romain Couillet, Mohamed Tamaazousti

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Random Matrix Theory for AI: From Theory to Practice. (Théorie des matrices aléatoires pour l'IA: De la théorie à la pratique).

Mohamed El Amine Seddik

PhD thesis, 2020

Learning More Universal Representations for Transfer-Learning.

Youssef Tamaazousti, Hervé Le Borgne, Céline Hudelot, Mohamed El Amine Seddik, Mohamed Tamaazousti

IEEE Trans. Pattern Anal. Mach. Intell., 2020

Generative collaborative networks for single image super-resolution.

Mohamed El Amine Seddik, Mohamed Tamaazousti, John Lin

Neurocomputing, 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

Proceedings of the 37th International Conference on Machine Learning, 2020

Lightweight Neural Networks From PCA & LDA Based Distilled Dense Neural Networks.

Mohamed El Amine Seddik, Hassane Essafi, Abdallah Benzine, Mohamed Tamaazousti

Proceedings of the IEEE International Conference on Image Processing, 2020

2019

Deep Multi-class Adversarial Specularity Removal.

John Lin, Mohamed El Amine Seddik, Mohamed Tamaazousti, Youssef Tamaazousti, Adrien Bartoli

Proceedings of the Image Analysis - 21st Scandinavian Conference, 2019

A Kernel Random Matrix-Based Approach for Sparse PCA.

Mohamed El Amine Seddik, Mohamed Tamaazousti, Romain Couillet

Proceedings of the 7th International Conference on Learning Representations, 2019

Kernel Random Matrices of Large Concentrated Data: the Example of GAN-Generated Images.

Mohamed El Amine Seddik, Mohamed Tamaazousti, Romain Couillet

Proceedings of the IEEE International Conference on Acoustics, 2019

2018

From outage probability to ALOHA MAC layer performance analysis in distributed WSNs.

Mohamed El Amine Seddik, Viktor Toldov, Laurent Clavier, Nathalie Mitton

Proceedings of the 2018 IEEE Wireless Communications and Networking Conference, 2018