Seddik, Mohamed El Amine

11 publications

ICLR 2025 Maximizing the Potential of Synthetic Data: Insights from Random Matrix Theory Aymane El Firdoussi, Mohamed El Amine Seddik, Soufiane Hayou, Reda Alami, Ahmed Alzubaidi, Hakim Hacid

ICLRW 2025 Synthetic Data Pruning in High Dimensions: A Random Matrix Perspective Aymane El Firdoussi, Mohamed El Amine Seddik, Soufiane Hayou, Reda Alami, Ahmed Alzubaidi, Hakim Hacid

ICMLW 2024 A Random Matrix Analysis of Learning with Noisy Labels Aymane El Firdoussi, Mohamed El Amine Seddik

CVPR 2024 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

ICLR 2024 Performance Gaps in Multi-View Clustering Under the Nested Matrix-Tensor Model Hugo Lebeau, Mohamed El Amine Seddik, José Henrique De Morais Goulart

UAI 2023 Learning from Low Rank Tensor Data: A Random Tensor Theory Perspective Mohamed El Amine Seddik, Malik Tiomoko, Alexis Decurninge, Maxim Panov, Maxime Gauillaud

ICML 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

AAAI 2022 Neural Networks Classify Through the Class-Wise Means of Their Representations Mohamed El Amine Seddik, Mohamed Tamaazousti

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

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