Diyuan Wu
3 Publications
2025 |
Published |
Conference Paper |
IST-REx-ID: 21326 |
Wu D, Mondelli M. Neural collapse beyond the unconstrained features model: Landscape, dynamics, and generalization in the mean-field regime. In: Proceedings of the 42nd International Conference on Machine Learning. Vol 267. ML Research Press; 2025:67499-67536.
[Published Version]
View
| Files available
| arXiv
2024 |
Published |
Conference Paper |
IST-REx-ID: 19518 |
Wu D, Modoranu I-V, Safaryan M, Kuznedelev D, Alistarh D-A. The iterative optimal brain surgeon: Faster sparse recovery by leveraging second-order information. In: 38th Conference on Neural Information Processing Systems. Vol 37. Neural Information Processing Systems Foundation; 2024.
[Preprint]
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| Download Preprint (ext.)
| arXiv
2023 |
Published |
Conference Paper |
IST-REx-ID: 14924 |
Wu D, Kungurtsev V, Mondelli M. Mean-field analysis for heavy ball methods: Dropout-stability, connectivity, and global convergence. In: Transactions on Machine Learning Research. ML Research Press; 2023.
[Published Version]
View
| Download Published Version (ext.)
| arXiv
Grants
3 Publications
2025 |
Published |
Conference Paper |
IST-REx-ID: 21326 |
Wu D, Mondelli M. Neural collapse beyond the unconstrained features model: Landscape, dynamics, and generalization in the mean-field regime. In: Proceedings of the 42nd International Conference on Machine Learning. Vol 267. ML Research Press; 2025:67499-67536.
[Published Version]
View
| Files available
| arXiv
2024 |
Published |
Conference Paper |
IST-REx-ID: 19518 |
Wu D, Modoranu I-V, Safaryan M, Kuznedelev D, Alistarh D-A. The iterative optimal brain surgeon: Faster sparse recovery by leveraging second-order information. In: 38th Conference on Neural Information Processing Systems. Vol 37. Neural Information Processing Systems Foundation; 2024.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
2023 |
Published |
Conference Paper |
IST-REx-ID: 14924 |
Wu D, Kungurtsev V, Mondelli M. Mean-field analysis for heavy ball methods: Dropout-stability, connectivity, and global convergence. In: Transactions on Machine Learning Research. ML Research Press; 2023.
[Published Version]
View
| Download Published Version (ext.)
| arXiv