| A field guide to federated optimization J Wang, Z Charles, Z Xu, G Joshi, HB McMahan, M Al-Shedivat, G Andrew, ... arXiv preprint arXiv:2107.06917, 2021 | 399 | 2021 |
| Adaptive quantization of model updates for communication-efficient federated learning D Jhunjhunwala, A Gadhikar, G Joshi, YC Eldar ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 129 | 2021 |
| Why random pruning is all we need to start sparse A Gadhikar, S Mukherjee, R Burkholz arXiv preprint arXiv:2210.02412, 2022 | 23 | 2022 |
| Leveraging spatial and temporal correlations in sparsified mean estimation D Jhunjhunwala, A Mallick, A Gadhikar, S Kadhe, G Joshi Advances in Neural Information Processing Systems 34, 14280-14292, 2021 | 18 | 2021 |
| Masks, signs, and learning rate rewinding A Gadhikar, R Burkholz arXiv preprint arXiv:2402.19262, 2024 | 6 | 2024 |
| Lottery tickets with nonzero biases J Fischer, A Gadhikar, R Burkholz arXiv preprint arXiv:2110.11150, 2021 | 4 | 2021 |
| Dynamical isometry for residual networks A Gadhikar, R Burkholz CISPA, 2022 | 2 | 2022 |
| Attention Is All You Need For Mixture-of-Depths Routing A Gadhikar, SK Majumdar, N Popp, P Saranrittichai, M Rapp, L Schott arXiv preprint arXiv:2412.20875, 2024 | | 2024 |
| Cyclic Sparse Training: Is it Enough? A Gadhikar, SH Nelaturu, R Burkholz arXiv preprint arXiv:2406.02773, 2024 | | 2024 |
| PaI is getting competitive by training longer A Gadhikar, SH Nelaturu, R Burkholz | | |
