27 citations · 44 across the 6 of their papers we have counts for
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cs.LG2019★ 27 cited
Privacy-Preserving Inference in Machine Learning Services Using Trusted Execution Environments
Krishna Giri Narra, Zhifeng Lin, Yongqin Wang +2
This work presents Origami, which provides privacy-preserving inference for large deep neural network (DNN) models through a combination of enclave execution, cryptographic blindin…
cs.LG2018★ 10 cited
GradiVeQ: Vector Quantization for Bandwidth-Efficient Gradient Aggregation in Distributed CNN Training
Mingchao Yu, Zhifeng Lin, Krishna Narra +6
Data parallelism can boost the training speed of convolutional neural networks (CNN), but could suffer from significant communication costs caused by gradient aggregation. To allev…