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Efficiency and Redundancy in Deep Learning Models: Theoretical Considerations and Practical Applications. (Efficience et redondance dans les modèles d'apprentissage profond : considérations théoriques et applications pratiques).. École normale supérieure de Lyon, France, (2021)LeViT: a Vision Transformer in ConvNet's Clothing for Faster Inference., , , , , , and . ICCV, page 12239-12249. IEEE, (2021)Low Bandwidth Video-Chat Compression using Deep Generative Models., , , , , , , , , and 2 other author(s). CoRR, (2020)Mixtral of Experts, , , , , , , , , and 16 other author(s). (2024)Equi-normalization of Neural Networks., , , and . ICLR (Poster), OpenReview.net, (2019)Training with Quantization Noise for Extreme Model Compression, , , , , , and . (2020)cite arxiv:2004.07320.EXACT: Extensive Attack for Split Learning., , , , and . CoRR, (2023)Low Bandwidth Video-Chat Compression Using Deep Generative Models., , , , , , , , , and 1 other author(s). CVPR Workshops, page 2388-2397. Computer Vision Foundation / IEEE, (2021)Mistral 7B., , , , , , , , , and 8 other author(s). CoRR, (2023)TAN Without a Burn: Scaling Laws of DP-SGD., , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 29937-29949. PMLR, (2023)