| Qsparse-local-SGD: Distributed SGD with quantization, sparsification and local computations D Basu, D Data, C Karakus, S Diggavi Advances in Neural Information Processing Systems 32, 2019 | 243 | 2019 |
| 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 | 137 | 2021 |
| Shuffled model of differential privacy in federated learning A Girgis, D Data, S Diggavi, P Kairouz, AT Suresh International Conference on Artificial Intelligence and Statistics, 2521-2529, 2021 | 72 | 2021 |
| SPARQ-SGD: Event-triggered and compressed communication in decentralized stochastic optimization N Singh, D Data, J George, S Diggavi arXiv preprint arXiv:1910.14280, 2019 | 41* | 2019 |
| Shuffled model of federated learning: Privacy, accuracy and communication trade-offs AM Girgis, D Data, S Diggavi, P Kairouz, AT Suresh IEEE journal on selected areas in information theory 2 (1), 464-478, 2021 | 35 | 2021 |
| Squarm-sgd: Communication-efficient momentum sgd for decentralized optimization N Singh, D Data, J George, S Diggavi IEEE Journal on Selected Areas in Information Theory 2 (3), 954-969, 2021 | 28 | 2021 |
| Communication and randomness lower bounds for secure computation D Data, VM Prabhakaran, MM Prabhakaran IEEE Transactions on Information Theory 62 (7), 3901-3929, 2016 | 22 | 2016 |
| On the communication complexity of secure computation D Data, MM Prabhakaran, VM Prabhakaran Advances in Cryptology–CRYPTO 2014: 34th Annual Cryptology Conference, Santa …, 2014 | 22 | 2014 |
| Byzantine-resilient SGD in high dimensions on heterogeneous data D Data, S Diggavi 2021 IEEE International Symposium on Information Theory (ISIT), 2310-2315, 2021 | 21 | 2021 |
| Data encoding for byzantine-resilient distributed optimization D Data, L Song, SN Diggavi IEEE Transactions on Information Theory 67 (2), 1117-1140, 2020 | 21 | 2020 |
| Byzantine-Resilient High-Dimensional SGD with Local Iterations on Heterogeneous Data D Data, S Diggavi International Conference on Machine Learning 139, 2478-2488, 2021 | 16 | 2021 |
| Data encoding for Byzantine-resilient distributed gradient descent D Data, L Song, S Diggavi 2018 56th Annual Allerton Conference on Communication, Control, and …, 2018 | 16 | 2018 |
| Data encoding methods for byzantine-resilient distributed optimization D Data, L Song, S Diggavi 2019 IEEE International Symposium on Information Theory (ISIT), 2719-2723, 2019 | 14 | 2019 |
| Must the communication graph of MPC protocols be an expander? E Boyle, R Cohen, D Data, P Hubáček Advances in Cryptology–CRYPTO 2018: 38th Annual International Cryptology …, 2018 | 14 | 2018 |
| Quped: Quantized personalization via distillation with applications to federated learning K Ozkara, N Singh, D Data, S Diggavi Advances in Neural Information Processing Systems 34, 3622-3634, 2021 | 13 | 2021 |
| On the rényi differential privacy of the shuffle model AM Girgis, D Data, S Diggavi, AT Suresh, P Kairouz Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications …, 2021 | 13 | 2021 |
| Differentially private federated learning with shuffling and client self-sampling AM Girgis, D Data, S Diggavi 2021 IEEE International Symposium on Information Theory (ISIT), 338-343, 2021 | 10 | 2021 |
| Byzantine-tolerant distributed coordinate descent D Data, S Diggavi 2019 IEEE International Symposium on Information Theory (ISIT), 2724-2728, 2019 | 7 | 2019 |
| How to securely compute the modulo-two sum of binary sources D Data, BK Dey, M Mishra, VM Prabhakaran 2014 IEEE Information Theory Workshop (ITW 2014), 496-500, 2014 | 7 | 2014 |
| Towards characterizing securely computable two-party randomized functions D Data, M Prabhakaran Public-Key Cryptography–PKC 2018: 21st IACR International Conference on …, 2018 | 6 | 2018 |
Suhas DiggaviUCLAVerified email at ee.ucla.edu
