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ORCIDKarthik Garimella
- > Home > Persons > Karthik Garimella
Publications
- 2025
[c4]Austin Ebel
, Karthik Garimella, Brandon Reagen:
Orion: A Fully Homomorphic Encryption Framework for Deep Learning. ASPLOS (2) 2025: 734-749- [i10]Karthik Garimella, Austin Ebel, Gabrielle De Micheli, Brandon Reagen:
HE-LRM: Encrypted Deep Learning Recommendation Models using Fully Homomorphic Encryption. CoRR abs/2506.18150 (2025) - [i9]Karthik Garimella, Austin Ebel, Brandon Reagen:
EinHops: Einsum Notation for Expressive Homomorphic Operations on RNS-CKKS Tensors. CoRR abs/2507.07972 (2025) - [i8]Karthik Garimella, Austin Ebel, Brandon Reagen:
EinHops: Einsum Notation for Expressive Homomorphic Operations on RNS-CKKS Tensors. IACR Cryptol. ePrint Arch. 2025: 1272 (2025) - 2024
- [i7]Patrick Yubeaton, Jianqiao Mo, Karthik Garimella, Nandan Kumar Jha, Brandon Reagen, Chinmay Hegde, Siddharth Garg:
TruncFormer: Private LLM Inference Using Only Truncations. CoRR abs/2412.01042 (2024) - 2023
- [c3]Karthik Garimella, Zahra Ghodsi, Nandan Kumar Jha, Siddharth Garg, Brandon Reagen:
Characterizing and Optimizing End-to-End Systems for Private Inference. ASPLOS (3) 2023: 89-104 - [c2]Jianqiao Mo, Karthik Garimella, Negar Neda, Austin Ebel, Brandon Reagen:
Towards Fast and Scalable Private Inference. CF 2023: 322-328 - [i6]Jianqiao Mo, Karthik Garimella, Negar Neda, Austin Ebel, Brandon Reagen:
Towards Fast and Scalable Private Inference. CoRR abs/2307.04077 (2023) - [i5]Austin Ebel, Karthik Garimella, Brandon Reagen:
Orion: A Fully Homomorphic Encryption Compiler for Private Deep Neural Network Inference. CoRR abs/2311.03470 (2023) - 2022
- [i4]Karthik Garimella, Zahra Ghodsi, Nandan Kumar Jha, Siddharth Garg, Brandon Reagen:
Characterizing and Optimizing End-to-End Systems for Private Inference. CoRR abs/2207.07177 (2022) - 2021
- [i3]Karthik Garimella, Nandan Kumar Jha, Brandon Reagen:
Sisyphus: A Cautionary Tale of Using Low-Degree Polynomial Activations in Privacy-Preserving Deep Learning. CoRR abs/2107.12342 (2021) - [i2]Karthik Garimella, Nandan Kumar Jha, Zahra Ghodsi, Siddharth Garg, Brandon Reagen:
CryptoNite: Revealing the Pitfalls of End-to-End Private Inference at Scale. CoRR abs/2111.02583 (2021)
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last updated on 2025-08-13 21:21 CEST by the dblp team
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