Sisyphus: A Cautionary Tale of Using Low-Degree Polynomial Activations in Privacy-Preserving Deep Learning

26 July 2021

Karthik Garimella

Papers citing "Sisyphus: A Cautionary Tale of Using Low-Degree Polynomial Activations in Privacy-Preserving Deep Learning"

35 / 35 papers shown

Title
Precise Approximation of Convolutional Neural Networks for Homomorphically Encrypted Data Junghyun Lee Eunsang Lee Joon-Woo Lee Yongjune Kim Young-Sik Kim Jong-Seon No 87 58 0 23 May 2021
DeepReDuce: ReLU Reduction for Fast Private Inference N. Jha Zahra Ghodsi S. Garg Brandon Reagen 70 91 0 02 Mar 2021
CrypTFlow2: Practical 2-Party Secure Inference Deevashwer Rathee Mayank Rathee Nishant Kumar Nishanth Chandran Divya Gupta Aseem Rastogi Rahul Sharma 120 314 0 13 Oct 2020
CryptoNAS: Private Inference on a ReLU Budget Zahra Ghodsi A. Veldanda Brandon Reagen S. Garg 53 87 0 15 Jun 2020
BLAZE: Blazing Fast Privacy-Preserving Machine Learning A. Patra Ajith Suresh 61 197 0 18 May 2020
Dynamic ReLU Yinpeng Chen Xiyang Dai Mengchen Liu Dongdong Chen Lu Yuan Zicheng Liu 235 165 0 22 Mar 2020
Trident: Efficient 4PC Framework for Privacy Preserving Machine Learning Harsh Chaudhari Rahul Rachuri Ajith Suresh 69 214 0 05 Dec 2019
ASTRA: High Throughput 3PC over Rings with Application to Secure Prediction Harsh Chaudhari Ashish Choudhury A. Patra Ajith Suresh 48 130 0 05 Dec 2019
PyTorch: An Imperative Style, High-Performance Deep Learning Library Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury ... Sasank Chilamkurthy Benoit Steiner Lu Fang Junjie Bai Soumith Chintala ODL 493 42,449 0 03 Dec 2019
Mish: A Self Regularized Non-Monotonic Activation Function Diganta Misra 63 680 0 23 Aug 2019
Padé Activation Units: End-to-end Learning of Flexible Activation Functions in Deep Networks Alejandro Molina P. Schramowski Kristian Kersting ODL 34 80 0 15 Jul 2019
XONN: XNOR-based Oblivious Deep Neural Network Inference M. Riazi Mohammad Samragh Hao Chen Kim Laine Kristin E. Lauter F. Koushanfar FedML GNN BDL 56 282 0 19 Feb 2019
Towards Federated Learning at Scale: System Design Keith Bonawitz Hubert Eichner W. Grieskamp Dzmitry Huba A. Ingerman ... H. B. McMahan Timon Van Overveldt David Petrou Daniel Ramage Jason Roselander FedML 121 2,666 0 04 Feb 2019
Faster CryptoNets: Leveraging Sparsity for Real-World Encrypted Inference Edward Chou Josh Beal Daniel Levy Serena Yeung Albert Haque Li Fei-Fei 47 198 0 25 Nov 2018
Towards the AlexNet Moment for Homomorphic Encryption: HCNN, theFirst Homomorphic CNN on Encrypted Data with GPUs Ahmad Al Badawi Jin Chao Jie Lin Chan Fook Mun Sim Jun Jie B. Tan Xiao Nan Khin Mi Mi Aung V. Chandrasekhar 55 64 0 02 Nov 2018
GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration Jacob R. Gardner Geoff Pleiss D. Bindel Kilian Q. Weinberger A. Wilson GP 136 1,100 0 28 Sep 2018
TAPAS: Tricks to Accelerate (encrypted) Prediction As a Service Amartya Sanyal Matt J. Kusner Adria Gascon Varun Kanade FedML 63 127 0 09 Jun 2018
Slalom: Fast, Verifiable and Private Execution of Neural Networks in Trusted Hardware Florian Tramèr Dan Boneh FedML 171 397 0 08 Jun 2018
Chiron: Privacy-preserving Machine Learning as a Service T. Hunt Congzheng Song Reza Shokri Vitaly Shmatikov Emmett Witchel 44 201 0 15 Mar 2018
Gazelle: A Low Latency Framework for Secure Neural Network Inference Chiraag Juvekar Vinod Vaikuntanathan A. Chandrakasan 60 892 0 16 Jan 2018
Chameleon: A Hybrid Secure Computation Framework for Machine Learning Applications M. Riazi Christian Weinert Oleksandr Tkachenko Ebrahim M. Songhori T. Schneider F. Koushanfar FedML 46 494 0 10 Jan 2018
CryptoDL: Deep Neural Networks over Encrypted Data Ehsan Hesamifard Hassan Takabi Mehdi Ghasemi 55 380 0 14 Nov 2017
Self-Normalizing Neural Networks Günter Klambauer Thomas Unterthiner Andreas Mayr Sepp Hochreiter 455 2,516 0 08 Jun 2017
DeepSecure: Scalable Provably-Secure Deep Learning B. Rouhani M. Riazi F. Koushanfar FedML 52 415 0 24 May 2017
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications Andrew G. Howard Menglong Zhu Bo Chen Dmitry Kalenichenko Weijun Wang Tobias Weyand M. Andreetto Hartwig Adam 3DH 1.1K 20,837 0 17 Apr 2017
Federated Learning: Strategies for Improving Communication Efficiency Jakub Konecný H. B. McMahan Felix X. Yu Peter Richtárik A. Suresh Dave Bacon FedML 303 4,646 0 18 Oct 2016
Deep Learning with Differential Privacy Martín Abadi Andy Chu Ian Goodfellow H. B. McMahan Ilya Mironov Kunal Talwar Li Zhang FedML SyDa 205 6,121 0 01 Jul 2016
Gaussian Error Linear Units (GELUs) Dan Hendrycks Kevin Gimpel 169 5,000 0 27 Jun 2016
Understanding and Improving Convolutional Neural Networks via Concatenated Rectified Linear Units Wenling Shang Kihyuk Sohn Diogo Almeida Honglak Lee 72 505 0 16 Mar 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.2K 194,020 0 10 Dec 2015
Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs) Djork-Arné Clevert Thomas Unterthiner Sepp Hochreiter 300 5,524 0 23 Nov 2015
Empirical Evaluation of Rectified Activations in Convolutional Network Bing Xu Naiyan Wang Tianqi Chen Mu Li 135 2,912 0 05 May 2015
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification Kaiming He Xinming Zhang Shaoqing Ren Jian Sun VLM 323 18,625 0 06 Feb 2015
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 1.6K 100,386 0 04 Sep 2014
Practical Bayesian Optimization of Machine Learning Algorithms Jasper Snoek Hugo Larochelle Ryan P. Adams 353 7,942 0 13 Jun 2012