形式的検証

Adversarial Robustness of Deep Neural Networks: A Survey from a Formal Verification Perspective

Authors: Mark Huasong Meng, Guangdong Bai, Sin Gee Teo, Zhe Hou, Yan Xiao, Yun Lin, Jin Song Dong | Published: 2022-06-24 | Updated: 2022-10-11
アルゴリズム設計
形式的検証
敵対的サンプル

Sampling without Replacement Leads to Faster Rates in Finite-Sum Minimax Optimization

Authors: Aniket Das, Bernhard Schölkopf, Michael Muehlebach | Published: 2022-06-07 | Updated: 2022-10-10
収束性分析
形式的検証
関数の定義

SoK: Certified Robustness for Deep Neural Networks

Authors: Linyi Li, Tao Xie, Bo Li | Published: 2020-09-09 | Updated: 2023-04-12
形式的検証
深層学習技術
脆弱性評価手法

Adversarial Learning Guarantees for Linear Hypotheses and Neural Networks

Authors: Pranjal Awasthi, Natalie Frank, Mehryar Mohri | Published: 2020-04-28
ロバスト性向上手法
形式的検証
敵対的攻撃検出

Slalom: Fast, Verifiable and Private Execution of Neural Networks in Trusted Hardware

Authors: Florian Tramèr, Dan Boneh | Published: 2018-06-08 | Updated: 2019-02-27
プライバシー保護手法
形式的検証
深層学習技術