| Optimal Complexity in Decentralized Training Y Lu, C De Sa International Conference on Machine Learning, 7111-7123, 2020 | 88 | 2020 |
| Moniqua: Modulo Quantized Communication in Decentralized SGD Y Lu, C De Sa International Conference on Machine Learning, 6415-6425, 2020 | 68 | 2020 |
| Cocktailsgd: Fine-tuning foundation models over 500mbps networks J Wang, Y Lu, B Yuan, B Chen, P Liang, C De Sa, C Re, C Zhang International Conference on Machine Learning, 36058-36076, 2023 | 36 | 2023 |
| Hyperparameter optimization is deceiving us, and how to stop it AF Cooper, Y Lu, J Forde, CM De Sa Advances in Neural Information Processing Systems 34, 3081-3095, 2021 | 34 | 2021 |
| Variance Reduced Training with Stratified Sampling for Forecasting Models Y Lu, Y Park, L Chen, Y Wang, C De Sa, D Foster International Conference on Machine Learning, 7145-7155, 2021 | 24 | 2021 |
| Maximizing communication efficiency for large-scale training via 0/1 adam Y Lu, C Li, M Zhang, C De Sa, Y He arXiv preprint arXiv:2202.06009, 2022 | 22 | 2022 |
| A general analysis of example-selection for stochastic gradient descent Y Lu, SY Meng, C De Sa International Conference on Learning Representations (ICLR) 10, 2022 | 22 | 2022 |
| Adaptive diffusion of sensitive information in online social networks X Wu, L Fu, H Long, D Yang, Y Lu, X Wang, G Chen IEEE Transactions on Knowledge and Data Engineering 33 (8), 3020-3034, 2020 | 20 | 2020 |
| GraB: Finding Provably Better Data Permutations than Random Reshuffling Y Lu, W Guo, CM De Sa Advances in Neural Information Processing Systems 35, 8969-8981, 2022 | 19 | 2022 |
| STEP: learning N: M structured sparsity masks from scratch with precondition Y Lu, S Agrawal, S Subramanian, O Rybakov, C De Sa, A Yazdanbakhsh International Conference on Machine Learning, 22812-22824, 2023 | 13 | 2023 |
| Mixml: A unified analysis of weakly consistent parallel learning Y Lu, J Nash, C De Sa arXiv preprint arXiv:2005.06706, 2020 | 11 | 2020 |
| Coordinating distributed example orders for provably accelerated training AF Cooper, W Guo, K Pham, T Yuan, CF Ruan, Y Lu, C De Sa Thirty-seventh Conference on Neural Information Processing Systems, 2023 | 4* | 2023 |
| Decentralized learning: Theoretical optimality and practical improvements Y Lu, C De Sa Journal of Machine Learning Research 24 (93), 1-62, 2023 | 3 | 2023 |
| Provably Efficient Model Training Over Centralized and Decentralized Datasets Y Lu Cornell University, 2023 | | 2023 |
