minimax optimization

The complexity of nonconvex-strongly-concave minimax optimization UAI 2021 Thinking Inside the Ball: Near-Optimal Minimization of the Maximal Loss COLT 2021 Train simultaneously, generalize better: Stability of gradient-based minimax learners ICML 2021 Understanding Over-parameterization in Generative Adversarial Networks ICLR 2021 Uniform-PAC Bounds for Reinforcement Learning with Linear Function Approximation NeurIPS 2021 A Catalyst Framework for Minimax Optimization NeurIPS 2020 Adversarial Distributional Training for Robust Deep Learning NeurIPS 2020 A Swiss Army Knife for Minimax Optimal Transport ICML 2020 Calibrated Surrogate Losses for Adversarially Robust Classification COLT 2020 Distributionally Robust Federated Averaging NeurIPS 2020 Do GANs always have Nash equilibria? ICML 2020 Fairness for Robust Log Loss Classification AAAI 2020 Generative Adversarial Imitation Learning with Neural Network Parameterization: Global Optimality and Convergence Rate ICML 2020 Global Convergence and Variance Reduction for a Class of Nonconvex-Nonconcave Minimax Problems NeurIPS 2020 Hybrid Variance-Reduced SGD Algorithms For Minimax Problems with Nonconvex-Linear Function NeurIPS 2020 Improved Algorithms for Convex-Concave Minimax Optimization NeurIPS 2020 Lower Complexity Bounds for Finite-Sum Convex-Concave Minimax Optimization Problems ICML 2020 Minimax Dynamics of Optimally Balanced Spiking Networks of Excitatory and Inhibitory Neurons NeurIPS 2020 Minimax Estimation of Conditional Moment Models NeurIPS 2020 Minimax Pareto Fairness: A Multi Objective Perspective ICML 2020 Near-Optimal Algorithms for Minimax Optimization COLT 2020 On Computation and Generalization of Generative Adversarial Imitation Learning ICLR 2020 On Gradient Descent Ascent for Nonconvex-Concave Minimax Problems ICML 2020 Online learning with dynamics: A minimax perspective NeurIPS 2020 On Solving Minimax Optimization Locally: A Follow-the-Ridge Approach ICLR 2020