Sample Compression Hypernetworks: From Generalization Bounds to Meta-Learning.
Benjamin Leblanc, Mathieu Bazinet, Nathaniel D'Amours, Alexandre Drouin, Pascal Germain
Version arXiv du papier
Mes publications
Vous pouvez trouver tous mes articles sur mon profil Google Scholar.
Articles
Sample Compression Unleashed : New Generalization Bounds for Real Valued Losses.
Mathieu Bazinet, Valentina Zantedeschi, Pascal Germain
Version arXiv du papier Code du papier
Wavelet-Based Feature Map for Kernel Approximation.
Mathieu Bazinet, Valentina Zantedeschi, Pascal Germain
Cet article a été soumis en 2023, mais n'a jamais été publié. À venir!
Application of machine learning tools to study the synergistic impact of physicochemical properties of peptides and filtration membranes on peptide migration during electrodialysis with filtration membranes
Zain Sanchez-Reinoso, Mathieu Bazinet, Benjamin Leblanc, Jean-Pierre Clément, Pascal Germain, Laurent Bazinet.
Présentement en évaluation.
Code du papier
How peptide migration and fraction bioactivity are modulated by electrical current modes during separation by an electromembrane process: A comprehensive machine learning-based peptidomic approach.
Aurore Cournoyer, Mathieu Bazinet, Jean-Pierre Clément, Pier-Luc Plante, Ismail Fliss, Laurent Bazinet.
Publié dans la thèse d'Aurore Cournoyer. Présentement en évaluation.
Code du papier
Articles de workshop
Sample Compression Unleashed : New Generalization Bounds for Real Valued Losses.
Mathieu Bazinet, Valentina Zantedeschi, Pascal Germain
Papier accepté au Workshop on Mathematics of Modern Machine Learning de NeurIPS 2024.
Sample Compression Unleashed : New Generalization Bounds for Real Valued Losses.
Mathieu Bazinet, Valentina Zantedeschi, Pascal Germain
Papier accepté au Workshop on Machine Learning and Compression de NeurIPS 2024.
Sample Compression Hypernetworks: From Generalization Bounds to Meta-Learning.
Benjamin Leblanc, Mathieu Bazinet, Nathaniel D'Amours, Alexandre Drouin, Pascal Germain
Papier accepté au Workshop on Machine Learning and Compression de NeurIPS 2024.