1 code implementation • 26 May 2022 • Gilad Cohen, Raja Giryes
Member inference (MI) attacks aim to determine if a specific data sample was used to train a machine learning model.
1 code implementation • 1 Mar 2022 • Gilad Cohen, Raja Giryes
Generative Adversarial Networks (GANs) are very popular frameworks for generating high-quality data, and are immensely used in both the academia and industry in many domains.
2 code implementations • 16 Sep 2021 • Gilad Cohen, Raja Giryes
A leading defense against such attacks is adversarial training, a technique in which a DNN is trained to be robust to adversarial attacks by introducing adversarial noise to its input.
1 code implementation • CVPR 2020 • Gilad Cohen, Guillermo Sapiro, Raja Giryes
We use influence functions to measure the impact of every training sample on the validation set data.
1 code implementation • 31 Mar 2019 • Liat Sless, Gilad Cohen, Bat El Shlomo, Shaul Oron
Occupancy grid mapping is an important component in road scene understanding for autonomous driving.
no code implementations • 17 May 2018 • Gilad Cohen, Guillermo Sapiro, Raja Giryes
Moreover, the behavior of DNNs compared to the linear classifiers SVM and LR is quite the same on the training and test data regardless of whether the network generalizes.