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Karthik Prasad
Karthik Prasad
Training LLMs | Llama @ Meta
uci.edu üzerinde doğrulanmış e-posta adresine sahip
Başlık
Alıntı yapanlar
Alıntı yapanlar
Yıl
The llama 3 herd of models
A Grattafiori, A Dubey, A Jauhri, A Pandey, A Kadian, A Al-Dahle, ...
arXiv preprint arXiv:2407.21783, 2024
34462024
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
4102021
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
732021
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
72022
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
22023
Curating Semantic Linked Open Datasets for Software Engineering.
K Mahesh, A Nagarajan, AR Balevalachilu, K Prasad
ISWC (Posters & Demos), 61-64, 2013
12013
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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