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Sanjay Kariyappa
Sanjay Kariyappa
Sr. Research Scientist, NVIDIA
Verified email at nvidia.com - Homepage
Title
Cited by
Cited by
Year
Maze: Data-free model stealing attack using zeroth-order gradient estimation
S Kariyappa, A Prakash, MK Qureshi
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
1692021
Improving adversarial robustness of ensembles with diversity training
S Kariyappa, MK Qureshi
arXiv preprint arXiv:1901.09981, 2019
1542019
Defending against model stealing attacks with adaptive misinformation
S Kariyappa, MK Qureshi
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
1242020
Reducing the impact of phase-change memory conductance drift on the inference of large-scale hardware neural networks
S Ambrogio, M Gallot, K Spoon, H Tsai, C Mackin, M Wesson, ...
2019 IEEE International Electron Devices Meeting (IEDM), 6.1. 1-6.1. 4, 2019
672019
Enabling transparent memory-compression for commodity memory systems
V Young, S Kariyappa, MK Qureshi
2019 IEEE International Symposium on High Performance Computer Architecture …, 2019
40*2019
Noise-resilient DNN: tolerating noise in PCM-based AI accelerators via noise-aware training
S Kariyappa, H Tsai, K Spoon, S Ambrogio, P Narayanan, C Mackin, ...
IEEE Transactions on Electron Devices 68 (9), 4356-4362, 2021
372021
Protecting dnns from theft using an ensemble of diverse models
S Kariyappa, A Prakash, MK Qureshi
International Conference on Learning Representations, 2021
342021
Exploit: Extracting private labels in split learning
S Kariyappa, MK Qureshi
2023 IEEE conference on secure and trustworthy machine learning (SaTML), 165-175, 2023
30*2023
Bespoke cache enclaves: Fine-grained and scalable isolation from cache side-channels via flexible set-partitioning
G Saileshwar, S Kariyappa, M Qureshi
2021 International Symposium on Secure and Private Execution Environment …, 2021
272021
Cocktail party attack: Breaking aggregation-based privacy in federated learning using independent component analysis
S Kariyappa, C Guo, K Maeng, W Xiong, GE Suh, MK Qureshi, HHS Lee
International Conference on Machine Learning, 15884-15899, 2023
262023
Measuring and controlling split layer privacy leakage using fisher information
K Maeng, C Guo, S Kariyappa, E Suh
arXiv preprint arXiv:2209.10119, 2022
72022
Bounding the invertibility of privacy-preserving instance encoding using fisher information
K Maeng, C Guo, S Kariyappa, GE Suh
Advances in Neural Information Processing Systems 36, 2024
52024
Information flow control in machine learning through modular model architecture
T Tiwari, S Gururangan, C Guo, W Hua, S Kariyappa, U Gupta, W Xiong, ...
33rd USENIX Security Symposium (USENIX Security 24), 6921-6938, 2024
52024
Privacy-Preserving Algorithmic Recourse
S Pentyala, S Sharma, S Kariyappa, F Lecue, D Magazzeni
arXiv preprint arXiv:2311.14137, 2023
52023
Enabling inference privacy with adaptive noise injection
S Kariyappa, O Dia, MK Qureshi
arXiv preprint arXiv:2104.02261, 2021
42021
Drift regularization to counteract variation in drift coefficients for analog accelerators
H Tsai, S Kariyappa
US Patent 11,514,326, 2022
22022
Neural network accelerators resilient to conductance drift
H Tsai, S Ambrogio, S Kariyappa, M Gallot
US Patent App. 17/035,005, 2022
12022
Progressive Inference: Explaining Decoder-Only Sequence Classification Models Using Intermediate Predictions
S Kariyappa, F Lécué, S Mishra, C Pond, D Magazzeni, M Veloso
arXiv preprint arXiv:2406.02625, 2024
2024
SHAP@ k: Efficient and Probably Approximately Correct (PAC) Identification of Top-k Features
S Kariyappa, L Tsepenekas, F Lécué, D Magazzeni
Proceedings of the AAAI Conference on Artificial Intelligence 38 (12), 13068 …, 2024
2024
2021 International Symposium on Secure and Private Execution Environment Design (SEED)| 978-1-6654-2025-9/21/$31.00© 2021 IEEE| DOI: 10.1109/SEED51797. 2021.00034
A Aharon, I Akturk, FA Andargie, MA Arroyo, T Austin, A Awad, L Biernacki, ...
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