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Van-Tam NGUYEN: some recent publications
“Till the Layers Collapse: Compressing a Deep Neural Network Through the Lenses of Batch Normalization Layers.” In Proceedings of the 39th AAAI Conference on Artificial Intelligence (AAAI 2025). AAAI Press, 2025
Nguyen, Le-Trung, Aël Quélennec, Enzo Tartaglione, Samuel Tardieu, and Van-Tam Nguyen. ”Activation Map Compression through Tensor Decomposition for Deep Learning.” In The Thirty-eighth Annual Conference on Neural Information Processing Systems, 2024.
Lorenzo Guerra, Linhan Xu, Paolo Bellavista, Thomas Chapuis, Guillaume Duc, Pavlo Mozharovskyi, and Van-Tam Nguyen. "AI-Driven Intrusion Detection Systems (IDS) on the ROAD Dataset: A Comparative Analysis for Automotive Controller Area Network (CAN)." In Proceedings of the 2024 Cyber Security in CarS Workshop, pp. 39-49. 2024.
Rémi Nahon, Ivan Luiz De Moura Matos, Van-Tam Nguyen, and Enzo Tartaglione. ”Debiasing surgeon: fantastic weights and how to find them.” In European Conference on Computer Vision, pp. 435-452. Springer, Cham, 2024.
Quélennec, Aël, Enzo Tartaglione, Pavlo Mozharovskyi, and Van-Tam Nguyen. ”Towards
On-device Learning on the Edge: Ways to Select Neurons to Update under a Budget
Constraint.” In Proceedings of the IEEE/CVF Winter Conference on
Applications of Computer Vision, pp. 685-694. 2024.
Rémi Nahon,
Van-Tam Nguyen, and Enzo Tartaglione. ”Mining
bias-target Alignment from Voronoi Cells.” In Proceedings of the IEEE/CVF International Conference on
Computer Vision, pp.
4946-4955. 2023.
Ziyu Li, Enzo Tartaglione,
and Van-Tam Nguyen. ”SCoTTi: Save Computation at Training Time with an adaptive
framework.” In Proceedings of the IEEE/CVF International Conference on
Computer Vision, pp.
1443-1452. 2023.
Zhu Liao, Victor Quétu, Van-Tam
Nguyen, and Enzo Tartaglione. ”Can
Unstructured Pruning Reduce the Depth in Deep Neural Networks?.” In Proceedings of the IEEE/CVF
International Conference on Computer Vision, pp. 1402-1406. 2023
Giovanna “Mental state classification using EEG signals: ethics, law and challenges.” In European Conference on Machine Learning and Principles and Practice of Knowledge Discovery - workshop track, 2023.
“AIoT-based Neural Decoding and Neurofeedback for
Accelerated Cognitive Training: Vision, Directions and Preliminary
Results.” In 2023 IEEE Statistical Signal Processing Workshop (SSP), pp. 705-709. IEEE, 2023.
”Optimized
preprocessing and Tiny ML for Attention State Classification.”
In 2023 IEEE Statistical Signal Processing Workshop (SSP), pp. 695-699. IEEE, 2023.
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