Literature Database

Defending against Backdoors in Federated Learning with Robust Learning Rate

Authors: Mustafa Safa Ozdayi, Murat Kantarcioglu, Yulia R. Gel | Published: 2020-07-07 | Updated: 2021-07-29
Backdoor Attack
Adversarial Learning
Defense Mechanism

Backdoor attacks and defenses in feature-partitioned collaborative learning

Authors: Yang Liu, Zhihao Yi, Tianjian Chen | Published: 2020-07-07
Poisoning
Adversarial Learning
Defense Mechanism

Stochastic Linear Bandits Robust to Adversarial Attacks

Authors: Ilija Bogunovic, Arpan Losalka, Andreas Krause, Jonathan Scarlett | Published: 2020-07-07 | Updated: 2020-10-27
Quantification of Uncertainty
Adversarial Learning
Computational Efficiency

Robust Learning with Frequency Domain Regularization

Authors: Weiyu Guo, Yidong Ouyang | Published: 2020-07-07
Adversarial Learning
Fundamentals of Machine Learning
Computational Efficiency

Regional Image Perturbation Reduces $L_p$ Norms of Adversarial Examples While Maintaining Model-to-model Transferability

Authors: Utku Ozbulak, Jonathan Peck, Wesley De Neve, Bart Goossens, Yvan Saeys, Arnout Van Messem | Published: 2020-07-07 | Updated: 2020-07-18
Attack Pattern Extraction
Adversarial Example
Adversarial Learning

Sharing Models or Coresets: A Study based on Membership Inference Attack

Authors: Hanlin Lu, Changchang Liu, Ting He, Shiqiang Wang, Kevin S. Chan | Published: 2020-07-06
Core Set Construction
Privacy Assessment
Membership Inference

Descent-to-Delete: Gradient-Based Methods for Machine Unlearning

Authors: Seth Neel, Aaron Roth, Saeed Sharifi-Malvajerdi | Published: 2020-07-06
Data Deletion Algorithm
Machine learning
Improvement of Learning

Certifying Decision Trees Against Evasion Attacks by Program Analysis

Authors: Stefano Calzavara, Pietro Ferrara, Claudio Lucchese | Published: 2020-07-06
Program Analysis
Attack Pattern Extraction
Static Analysis

Black-box Adversarial Example Generation with Normalizing Flows

Authors: Hadi M. Dolatabadi, Sarah Erfani, Christopher Leckie | Published: 2020-07-06
Adversarial Learning
Challenges of Generative Models
Computational Efficiency

On Data Augmentation and Adversarial Risk: An Empirical Analysis

Authors: Hamid Eghbal-zadeh, Khaled Koutini, Paul Primus, Verena Haunschmid, Michal Lewandowski, Werner Zellinger, Bernhard A. Moser, Gerhard Widmer | Published: 2020-07-06
Poisoning
Risk Management
Adversarial Learning