| Importance of data loading pipeline in training deep neural networks M Zolnouri, X Li, VP Nia arXiv preprint arXiv:2005.02130, 2020 | 16 | 2020 |
| Rethinking pareto frontier for performance evaluation of deep neural networks VP Nia, A Ghaffari, M Zolnouri, Y Savaria arXiv preprint arXiv:2202.09275, 2022 | 6 | 2022 |
| Demystifying and generalizing binaryconnect T Dockhorn, Y Yu, E Sari, M Zolnouri, V Partovi Nia Advances in Neural Information Processing Systems 34, 13202-13216, 2021 | 5 | 2021 |
| Methods, systems, and media for random semi-structured row-wise pruning in neural networks V Courville, M Ahmadi, M Zolnouri US Patent 11,657,285, 2023 | 3 | 2023 |
| Efficient Training Under Limited Resources M Zolnouri, D Lakhmiri, C Tribes, E Sari, SL Digabel arXiv preprint arXiv:2301.09264, 2023 | | 2023 |
| Scaling Deep Networks with the Mesh Adaptive Direct Search algorithm D Lakhmiri, M Zolnouri, VP Nia, C Tribes, SL Digabel arXiv preprint arXiv:2301.06641, 2023 | | 2023 |
| Mahdi Zolnouri Xinlin Li VP Nia Edge Intelligence Workshop 711 (23), 1, 2020 | | 2020 |
