C2PI: An Efficient Crypto-Clear Two-Party Neural Network Private Inference
Author:
Affiliation:
1. University of Southern California,Department of Electrical and Computer Engineering,Los Angeles,CA,USA
2. Intel Labs,San Diego,USA
Funder
Air Force Research Laboratory
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10247654/10247655/10247682.pdf?arnumber=10247682
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2. RNA-ViT: Reduced-Dimension Approximate Normalized Attention Vision Transformers for Latency Efficient Private Inference;2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD);2023-10-28
3. SAL-ViT: Towards Latency Efficient Private Inference on ViT using Selective Attention Search with a Learnable Softmax Approximation;2023 IEEE/CVF International Conference on Computer Vision (ICCV);2023-10-01
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