収束分析

RESIST: Resilient Decentralized Learning Using Consensus Gradient Descent

Authors: Cheng Fang, Rishabh Dixit, Waheed U. Bajwa, Mert Gurbuzbalaban | Published: 2025-02-11
MITM攻撃
収束分析

LLM Safety Alignment is Divergence Estimation in Disguise

Authors: Rajdeep Haldar, Ziyi Wang, Qifan Song, Guang Lin, Yue Xing | Published: 2025-02-02
プロンプトインジェクション
収束分析
大規模言語モデル
安全性アライメント

Byzantine-Resilient Zero-Order Optimization for Communication-Efficient Heterogeneous Federated Learning

Authors: Maximilian Egger, Mayank Bakshi, Rawad Bitar | Published: 2025-01-31
収束保証
収束分析
通信効率

Heterogeneous Multi-Player Multi-Armed Bandits Robust To Adversarial Attacks

Authors: Akshayaa Magesh, Venugopal V. Veeravalli | Published: 2025-01-21
収束保証
収束分析
通信効率

Efficient Phishing URL Detection Using Graph-based Machine Learning and Loopy Belief Propagation

Authors: Wenye Guo, Qun Wang, Hao Yue, Haijian Sun, Rose Qingyang Hu | Published: 2025-01-12
ネットワーク脅威検出
フィッシング検出
収束分析

A General Recipe for Contractive Graph Neural Networks — Technical Report

Authors: Maya Bechler-Speicher, Moshe Eliasof | Published: 2024-11-04
アルゴリズム
収束分析
正則化

On the Geometry of Regularization in Adversarial Training: High-Dimensional Asymptotics and Generalization Bounds

Authors: Matteo Vilucchio, Nikolaos Tsilivis, Bruno Loureiro, Julia Kempe | Published: 2024-10-21
収束分析
敵対的訓練

Feature Averaging: An Implicit Bias of Gradient Descent Leading to Non-Robustness in Neural Networks

Authors: Binghui Li, Zhixuan Pan, Kaifeng Lyu, Jian Li | Published: 2024-10-14
収束分析
敵対的サンプル

How to beat a Bayesian adversary

Authors: Zihan Ding, Kexin Jin, Jonas Latz, Chenguang Liu | Published: 2024-07-11
収束分析
敵対的訓練
最適化問題

FullCert: Deterministic End-to-End Certification for Training and Inference of Neural Networks

Authors: Tobias Lorenz, Marta Kwiatkowska, Mario Fritz | Published: 2024-06-17 | Updated: 2024-09-11
セキュリティ保証
収束分析
最適化問題