| Opacus: User-friendly differential privacy library in PyTorch A Yousefpour, I Shilov, A Sablayrolles, D Testuggine, K Prasad, M Malek, ... NeurIPS 2021 Workshop Privacy in Machine Learning, 2021 | 250 | 2021 |
| Antipodes of label differential privacy: PATE and ALIBI M Malek Esmaeili, I Mironov, K Prasad, I Shilov, F Tramèr Advances in Neural Information Processing Systems 34, 6934-6945, 2021 | 56* | 2021 |
| Reconciling security and communication efficiency in federated learning K Prasad, S Ghosh, G Cormode, I Mironov, A Yousefpour, P Stock NeurIPS 2022 Workshop Federated Learning homepage, 2022 | 6 | 2022 |
| Pruning Compact ConvNets for Efficient Inference S Ghosh, K Prasad, X Dai, P Zhang, B Wu, G Cormode, P Vajda The 8th EMC2 - Energy Efficient Training and Inference of Transformer Based …, 2023 | 1 | 2023 |
| Curating Semantic Linked Open Datasets for Software Engineering. K Mahesh, A Nagarajan, AR Balevalachilu, K Prasad ISWC (Posters & Demos), 61-64, 2013 | 1 | 2013 |
| Differential Privacy Series Part 3 | Efficient Per-Sample Gradient Computation for More Layers in Opacus A Sablayrolles, A Yousefpour, K Prasad, P Romov, D Testuggine, I Shilov, ... https://pytorch.medium.com/differential-privacy-series-part-3-efficient-per …, 2022 | | 2022 |
| Differential Privacy Series Part 2 | Efficient Per-Sample Gradient Computation in Opacus A Sablayrolles, A Yousefpour, K Prasad, P Romov, D Testuggine, I Shilov, ... https://medium.com/pytorch/differential-privacy-series-part-2-efficient-per …, 2021 | | 2021 |
| Differential Privacy Series Part 1 | DP-SGD Algorithm Explained A Sablayrolles, A Yousefpour, K Prasad, P Romov, D Testuggine, I Shilov, ... https://medium.com/pytorch/differential-privacy-series-part-1-dp-sgd …, 2020 | | 2020 |
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