Mohamed El Amine Seddik
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
14
Venues
9
Active years
2018–2025
Best venue rank
A*
Where they publish
Papers
14 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ICLR | Maximizing the Potential of Synthetic Data: Insights from Random Matrix Theory. | Aymane El Firdoussi, Mohamed El Amine Seddik, Soufiane Hayou, Rda Alami, Ahmed Alzubaidi, Hakim Hacid |
| 2024 | CVPR | Do Vision and Language Encoders Represent the World Similarly? | Mayug Maniparambil, Raiymbek Akshulakov, Yasser Abdelaziz Dahou Djilali, Mohamed El Amine Seddik, Sanath Narayan, Karttikeya Mangalam, Noel E. O'Connor |
| 2024 | ICLR | Performance Gaps in Multi-view Clustering under the Nested Matrix-Tensor Model. | Hugo Lebeau, Mohamed El Amine Seddik, Jos Henrique de Morais Goulart |
| 2023 | UAI | Learning from Low Rank Tensor Data: A Random Tensor Theory Perspective. | Mohamed El Amine Seddik, Malik Tiomoko, Alexis Decurninge, Maxim Panov, Maxime Guillaud |
| 2022 | AAAI | Neural Networks Classify through the Class-Wise Means of Their Representations. | Mohamed El Amine Seddik, Mohamed Tamaazousti |
| 2022 | AISTATS | Node Feature Kernels Increase Graph Convolutional Network Robustness. | Mohamed El Amine Seddik, Changmin Wu, Johannes F. Lutzeyer, Michalis Vazirgiannis |
| 2022 | ICML | 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 |
| 2021 | AISTATS | The Unexpected Deterministic and Universal Behavior of Large Softmax Classifiers. | Mohamed El Amine Seddik, Cosme Louart, Romain Couillet, Mohamed Tamaazousti |
| 2021 | ICIP | Optimization-Based Neural Networks Compression. | Younes Tahiri, Mohamed El Amine Seddik, Mohamed Tamaazousti |
| 2020 | ICIP | Lightweight Neural Networks From PCA & LDA Based Distilled Dense Neural Networks. | Mohamed El Amine Seddik, Hassane Essafi, Abdallah Benzine, Mohamed Tamaazousti |
| 2020 | ICML | 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 |
| 2019 | ICASSP | Kernel Random Matrices of Large Concentrated Data: the Example of GAN-Generated Images. | Mohamed El Amine Seddik, Mohamed Tamaazousti, Romain Couillet |
| 2019 | ICLR | A Kernel Random Matrix-Based Approach for Sparse PCA. | Mohamed El Amine Seddik, Mohamed Tamaazousti, Romain Couillet |
| 2018 | WCNC | From outage probability to ALOHA MAC layer performance analysis in distributed WSNs. | Mohamed El Amine Seddik, Viktor Toldov, Laurent Clavier, Nathalie Mitton |