Making Models Shallow Again: Jointly Learning to Reduce Non-Linearity and Depth for Latency-Efficient Private Inference

26 April 2023

Papers citing "Making Models Shallow Again: Jointly Learning to Reduce Non-Linearity and Depth for Latency-Efficient Private Inference"

8 / 8 papers shown

Title
CiMNet: Towards Joint Optimization for DNN Architecture and Configuration for Compute-In-Memory Hardware Souvik Kundu Anthony Sarah Vinay Joshi O. J. Omer S. Subramoney 29 0 0 19 Feb 2024
Linearizing Models for Efficient yet Robust Private Inference Sreetama Sarkar Souvik Kundu P. Beerel AAML 17 0 0 08 Feb 2024
CoPriv: Network/Protocol Co-Optimization for Communication-Efficient Private Inference Wenxuan Zeng Meng Li Haichuan Yang Wen-jie Lu Runsheng Wang Ru Huang 23 6 0 03 Nov 2023
Mitigate Replication and Copying in Diffusion Models with Generalized Caption and Dual Fusion Enhancement Chenghao Li Dake Chen Yuke Zhang P. Beerel DiffM 33 7 0 13 Sep 2023
FakeSwarm: Improving Fake News Detection with Swarming Characteristics Jun Wu Xuesong Ye 25 2 0 30 May 2023
C2PI: An Efficient Crypto-Clear Two-Party Neural Network Private Inference Yuke Zhang Dake Chen Souvik Kundu Haomei Liu Ruiheng Peng P. Beerel 14 8 0 26 Apr 2023
DeepReShape: Redesigning Neural Networks for Efficient Private Inference N. Jha Brandon Reagen 36 10 0 20 Apr 2023
CryptGPU: Fast Privacy-Preserving Machine Learning on the GPU Sijun Tan Brian Knott Yuan Tian David J. Wu BDL FedML 57 184 0 22 Apr 2021