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Privacy concerns in client-server machine learning have given rise to private inference (PI), where neural inference occurs directly on encrypted inputs.
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Günter Klambauer, Thomas Unterthiner, Andreas Mayr, and Sepp Hochreiter. 2017 · 2017
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GAZELLE: A Low Latency Framework for Secure Neural Network Inference. In 27th USENIX Security Symposium (USENIX Security 18)
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DeepReDuce: ReLU Reduction for Fast Private Inference. In International Conference on Machine Learning
Nandan Kumar Jha, Zahra Ghodsi, Siddharth Garg, and Brandon Reagen. 2021 · 2021
Closest in time.
Precise Approximation of Convolutional NeuralNetworks for Homomorphically Encrypted Data
Junghyun Lee, Eunsang Lee, Joon-Woo Lee, Yongjune Kim, Young-Sik Kim, and Jong-Seon No. 2021 · 2021
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SAFENet: ASecure, ACCURATE AND FAST NEU-RAL NETWORK INFERENCE
Qian Lou, Yilin Shen, Hongxia Jin, and Lei Jiang. 2021 · 2021
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