Popular GitHub Repositories for Adversaries

Robust Reinforcement Learning with the Alternating Training of Learned Adversaries (ATLA) framework

Code implementing the experiments described in the NeurIPS 2018 paper "With Friends Like These, Who Needs Adversaries?".

Sageflow: Robust Federated Learning against Both Stragglers and Adversaries at NeurIPS'21

Code associated with Findings of EMNLP (2022) paper "Generating Textual Adversaries with Minimal Perturbation"

Thesis: Detecting Adversaries in DQNs and Computer Vision using Bayesian CNNs

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This is an implementation of AdversarialTraining against popular adversaries.

The game is a simulation of multiple agents with conflicting goals. The agents try to survive and move as many cells as they can. On the other hand their adversaries try to interrupt them.

Training robust models takes a looong time since generating adversaries is so expensive. We design a parallel algorithm for training large robust models using PyTorch C++/MPI and show it runs fast!

This study explores the vulnerability of the Federated Learning (FL) model where a portion of clients participating in the FL process is under the control of adversaries who don’t have access to the training data but can access the training model and its parameters.