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F-LEMMA: Fast Learning-Based Energy Management for Multi-/Many-Core Processors.

, , , , , и . IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 42 (2): 616-629 (февраля 2023)

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Karthik Arumugam

Kiran Garimella

Karthik Gururaj

Karthik Narasimhan

Karthik Baddam

 

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F-LEMMA: Fast Learning-Based Energy Management for Multi-/Many-Core Processors., , , , , и . IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 42 (2): 616-629 (февраля 2023)Sisyphus: A Cautionary Tale of Using Low-Degree Polynomial Activations in Privacy-Preserving Deep Learning., , и . CoRR, (2021)Characterizing and Optimizing End-to-End Systems for Private Inference., , , , и . ASPLOS (3), стр. 89-104. ACM, (2023)Attacking Vision-based Perception in End-to-End Autonomous Driving Models., , , , , и . CoRR, (2019)Orion: A Fully Homomorphic Encryption Compiler for Private Deep Neural Network Inference., , и . CoRR, (2023)F-LEMMA: Fast Learning-based Energy Management for Multi-/Many-core Processors., , , , и . MLCAD, стр. 43-48. ACM, (2020)CryptoNite: Revealing the Pitfalls of End-to-End Private Inference at Scale., , , , и . CoRR, (2021)Characterizing and Optimizing End-to-End Systems for Private Inference., , , , и . CoRR, (2022)Attacking vision-based perception in end-to-end autonomous driving models., , , , , и . J. Syst. Archit., (2020)Towards Fast and Scalable Private Inference., , , , и . CF, стр. 322-328. ACM, (2023)