Variation Spaces for Multi-Output Neural Networks: Insights on Multi-Task Learning and Network Compression J Shenouda, R Parhi, K Lee, RD Nowak Journal of Machine Learning Research 25, 1-40, 2024 | 16* | 2024 |
A Better Way to Decay: Proximal Gradient Training Algorithms for Neural Nets L Yang, J Zhang, J Shenouda, D Papailiopoulos, K Lee, RD Nowak NeurIPS 2022 Optimization for Machine Learning Workshop, 2022 | 6 | 2022 |
A Guide to Computational Reproducibility in Signal Processing and Machine Learning [Tips & Tricks] J Shenouda, WU Bajwa IEEE Signal Processing Magazine 40 (2), 141-151, 2023 | 5 | 2023 |
ReLUs Are Sufficient for Learning Implicit Neural Representations J Shenouda, Y Zhou, RD Nowak International Conference on Machine Learning 2024, 2024 | 3 | 2024 |
The Effects of Multi-Task Learning on ReLU Neural Network Functions J Nakhleh, J Shenouda, RD Nowak arXiv preprint arXiv:2410.21696, 2024 | 2 | 2024 |
A Continuous Transform for Localized Ridgelets J Shenouda, R Parhi, RD Nowak 2023 International Conference on Sampling Theory and Applications (SampTA), 1-5, 2023 | 1 | 2023 |
A New Neural Kernel Regime: The Inductive Bias of Multi-Task Learning JB Nakhleh, J Shenouda, RD Nowak The Thirty-eighth Annual Conference on Neural Information Processing Systems, 2024 | | 2024 |
PathProx: A Proximal Gradient Algorithm for Weight Decay Regularized Deep Neural Networks L Yang, J Zhang, J Shenouda, D Papailiopoulos, K Lee, RD Nowak arXiv preprint arXiv:2210.03069, 2022 | | 2022 |