A General Recipe for Contractive Graph Neural Networks — Technical Report
Authors: Maya Bechler-Speicher, Moshe Eliasof | Published: 2024-11-04
Regularization
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Regularization for Adversarial Robust Learning
Authors: Jie Wang, Rui Gao, Yao Xie | Published: 2024-08-19 | Updated: 2024-08-22
Variational Randomized Smoothing for Sample-Wise Adversarial Robustness
Authors: Ryo Hase, Ye Wang, Toshiaki Koike-Akino, Jing Liu, Kieran Parsons | Published: 2024-07-16
Hyperparameter Learning under Data Poisoning: Analysis of the Influence of Regularization via Multiobjective Bilevel Optimization
Authors: Javier Carnerero-Cano, Luis Muñoz-González, Phillippa Spencer, Emil C. Lupu | Published: 2023-06-02 | Updated: 2023-06-23
Understanding Overfitting in Adversarial Training via Kernel Regression
Authors: Teng Zhang, Kang Li | Published: 2023-04-13 | Updated: 2023-04-19
On Mitigating the Utility-Loss in Differentially Private Learning: A new Perspective by a Geometrically Inspired Kernel Approach
Authors: Mohit Kumar, Bernhard A. Moser, Lukas Fischer | Published: 2023-04-03 | Updated: 2024-02-07
The Geometry of Adversarial Training in Binary Classification
Authors: Leon Bungert, Nicolás García Trillos, Ryan Murray | Published: 2021-11-26 | Updated: 2022-08-01
Unrolling SGD: Understanding Factors Influencing Machine Unlearning
Authors: Anvith Thudi, Gabriel Deza, Varun Chandrasekaran, Nicolas Papernot | Published: 2021-09-27 | Updated: 2022-03-02
A Fairness Analysis on Private Aggregation of Teacher Ensembles
Authors: Cuong Tran, My H. Dinh, Kyle Beiter, Ferdinando Fioretto | Published: 2021-09-17