| XORing elephants: Novel erasure codes for big data M Sathiamoorthy, M Asteris, D Papailiopoulos, AG Dimakis, R Vadali, ... Proceedings of the VLDB Endowment 6 (5), 325-336, 2013 | 827 | 2013 |
| Speeding up distributed machine learning using codes K Lee, M Lam, R Pedarsani, D Papailiopoulos, K Ramchandran IEEE Transactions on Information Theory, 2017 | 681 | 2017 |
| Locally repairable codes DS Papailiopoulos, AG Dimakis IEEE Transactions on Information Theory 60 (10), 5843-5855, 2014 | 523 | 2014 |
| Federated Learning with Matched Averaging H Wang, M Yurochkin, Y Sun, D Papailiopoulos, Y Khazaeni ICLR 2020, 2020 | 318 | 2020 |
| Simple regenerating codes: Network coding for cloud storage DS Papailiopoulos, J Luo, AG Dimakis, C Huang, J Li 2012 Proceedings IEEE INFOCOM, 2801-2805, 2012 | 239 | 2012 |
| Locality and availability in distributed storage AS Rawat, DS Papailiopoulos, AG Dimakis, S Vishwanath IEEE Transactions on Information Theory 62 (8), 4481-4493, 2016 | 238 | 2016 |
| Atomo: Communication-efficient learning via atomic sparsification H Wang, S Sievert, S Liu, Z Charles, S Wright, D Papailiopoulos Advances in Neural Information Processing Systems 31, 9850-9861, 2018 | 224 | 2018 |
| Optimal locally repairable codes and connections to matroid theory I Tamo, DS Papailiopoulos, AG Dimakis IEEE Transactions on Information Theory 62 (12), 6661-6671, 2016 | 210 | 2016 |
| Interference alignment as a rank constrained rank minimization DS Papailiopoulos, AG Dimakis IEEE Transactions on Signal Processing 60 (8), 4278-4288, 2012 | 203 | 2012 |
| Repair optimal erasure codes through hadamard designs DS Papailiopoulos, AG Dimakis, VR Cadambe IEEE transactions on information theory 59 (5), 3021-3037, 2013 | 193 | 2013 |
| DRACO: Byzantine-resilient Distributed Training via Redundant Gradients L Chen, H Wang, Z Charles, D Papailiopoulos International Conference on Machine Learning, 902-911, 2018 | 189* | 2018 |
| Perturbed Iterate Analysis for Asynchronous Stochastic Optimization H Mania, X Pan, D Papailiopoulos, B Recht, K Ramchandran, MI Jordan SIAM Journal on Optimization 27 (4), 2202-2229, 2017 | 184 | 2017 |
| Attack of the tails: Yes, you really can backdoor federated learning H Wang, K Sreenivasan, S Rajput, H Vishwakarma, S Agarwal, J Sohn, ... Advances in Neural Information Processing Systems 33, 2020 | 126 | 2020 |
| Gradient Diversity: a Key Ingredient for Scalable Distributed Learning D Yin, A Pananjady, M Lam, D Papailiopoulos, K Ramchandran, P Bartlett Proceedings of the 21th International Conference on Artificial Intelligence …, 2018 | 104 | 2018 |
| Parallel Correlation Clustering on Big Graphs X Pan, D Papailiopoulos, S Oymak, B Recht, K Ramchandran, MI Jordan Advances in Neural Information Processing Systems, 82-90, 2015 | 88 | 2015 |
| Stability and generalization of learning algorithms that converge to global optima Z Charles, D Papailiopoulos International Conference on Machine Learning, 745-754, 2018 | 85 | 2018 |
| Provable Deterministic Leverage Score Sampling D Papailiopoulos, A Kyrillidis, C Boutsidis arXiv preprint arXiv:1404.1530, 2014 | 75 | 2014 |
| Sparse PCA through low-rank approximations D Papailiopoulos, A Dimakis, S Korokythakis International Conference on Machine Learning, 747-755, 2013 | 73 | 2013 |
| Approximate Gradient Coding via Sparse Random Graphs Z Charles, D Papailiopoulos, J Ellenberg arXiv preprint arXiv:1711.06771, 2017 | 65 | 2017 |
| DETOX: A Redundancy-based Framework for Faster and More Robust Gradient Aggregation S Rajput, H Wang, Z Charles, D Papailiopoulos Advances in Neural Information Processing Systems, 10320-10330, 2019 | 63 | 2019 |
Alexandros G DimakisProfessor, ECE University of Texas at Austinaustin.utexas.edu의 이메일 확인됨
