計算効率

Fast and Private Inference of Deep Neural Networks by Co-designing Activation Functions

Authors: Abdulrahman Diaa, Lucas Fenaux, Thomas Humphries, Marian Dietz, Faezeh Ebrahimianghazani, Bailey Kacsmar, Xinda Li, Nils Lukas, Rasoul Akhavan Mahdavi, Simon Oya, Ehsan Amjadian, Florian Kerschbaum | Published: 2023-06-14 | Updated: 2024-04-16
アルゴリズム
メンバーシップ推論
計算効率

Privacy-Aware Compression for Federated Learning Through Numerical Mechanism Design

Authors: Chuan Guo, Kamalika Chaudhuri, Pierre Stock, Mike Rabbat | Published: 2022-11-08 | Updated: 2023-08-10
プライバシー保護手法
最適化手法
計算効率

A Comprehensive Survey on Edge Data Integrity Verification: Fundamentals and Future Trends

Authors: Yao Zhao, Youyang Qu, Yong Xiang, Md Palash Uddin, Dezhong Peng, Longxiang Gao | Published: 2022-10-20 | Updated: 2024-08-07
セキュリティ分析
プライバシーリスク管理
計算効率

New Secure Sparse Inner Product with Applications to Machine Learning

Authors: Guowen Xu, Shengmin Xu, Jianting Ning, Tianwei Zhang, Xinyi Huang, Hongwei Li, Rongxing Lu | Published: 2022-10-16
セキュリティ分析
暗号学
計算効率

VerifyML: Obliviously Checking Model Fairness Resilient to Malicious Model Holder

Authors: Guowen Xu, Xingshuo Han, Gelei Deng, Tianwei Zhang, Shengmin Xu, Jianting Ning, Anjia Yang, Hongwei Li | Published: 2022-10-16
多者計算
暗号学
計算効率

Suppressing Poisoning Attacks on Federated Learning for Medical Imaging

Authors: Naif Alkhunaizi, Dmitry Kamzolov, Martin Takáč, Karthik Nandakumar | Published: 2022-07-15
ビザンチン耐性
ポイズニング攻撃
計算効率

How to Steer Your Adversary: Targeted and Efficient Model Stealing Defenses with Gradient Redirection

Authors: Mantas Mazeika, Bo Li, David Forsyth | Published: 2022-06-28
アルゴリズム設計
敵対的サンプル
計算効率

Parallel Instance Filtering for Malware Detection

Authors: Martin Jureček, Olha Jurečková | Published: 2022-06-28
アルゴリズム設計
計算効率
静的分析

Unlocking High-Accuracy Differentially Private Image Classification through Scale

Authors: Soham De, Leonard Berrada, Jamie Hayes, Samuel L. Smith, Borja Balle | Published: 2022-04-28 | Updated: 2022-06-16
プライバシー保護手法
モデル設計
計算効率

CrypTen: Secure Multi-Party Computation Meets Machine Learning

Authors: Brian Knott, Shobha Venkataraman, Awni Hannun, Shubho Sengupta, Mark Ibrahim, Laurens van der Maaten | Published: 2021-09-02 | Updated: 2022-09-15
メンバーシップ推論
機械学習手法
計算効率