projected gradient descent

Mind the Box: l_1-APGD for Sparse Adversarial Attacks on Image Classifiers ICML 2021 Natural continual learning: success is a journey, not (just) a destination NeurIPS 2021 Understanding Catastrophic Overfitting in Single-step Adversarial Training AAAI 2021 Adversarial Robustness Against the Union of Multiple Perturbation Models ICML 2020 A Flexible Latent Space Model for Multilayer Networks ICML 2020 A Frank-Wolfe Framework for Efficient and Effective Adversarial Attacks AAAI 2020 An efficient nonconvex reformulation of stagewise convex optimization problems NeurIPS 2020 Attacks Which Do Not Kill Training Make Adversarial Learning Stronger ICML 2020 Bayesian Adversarial Attack on Graph Neural Networks (Student Abstract) AAAI 2020 Fast is better than free: Revisiting adversarial training ICLR 2020 Guided Adversarial Attack for Evaluating and Enhancing Adversarial Defenses NeurIPS 2020 Partial Adversarial Behavior Deception in Security Games IJCAI 2020 Stronger and Faster Wasserstein Adversarial Attacks ICML 2020 Tree-projected gradient descent for estimating gradient-sparse parameters on graphs COLT 2020 Universal Latent Space Model Fitting for Large Networks with Edge Covariates JMLR 2020 Unsupervised Audio Source Separation Using Generative Priors Interspeech 2020 Computationally and Statistically Efficient Truncated Regression COLT 2019 Distributionally Adversarial Attack AAAI 2019 Efficiently testing local optimality and escaping saddles for ReLU networks ICLR 2019 GAN-Based Projector for Faster Recovery With Convergence Guarantees in Linear Inverse Problems ICCV 2019 Learning Sparse Distributions using Iterative Hard Thresholding NeurIPS 2019 Non-Convex Projected Gradient Descent for Generalized Low-Rank Tensor Regression JMLR 2019 On the Convergence and Robustness of Adversarial Training ICML 2019 Overcomplete Independent Component Analysis via SDP AISTATS 2019 Proximal Mean-Field for Neural Network Quantization ICCV 2019