convergence analysis

Regularized linear autoencoders recover the principal components, eventually NeurIPS 2020 Robust Deep Learning as Optimal Control: Insights and Convergence Guarantees L4DC 2020 Sequential Cooperative Bayesian Inference ICML 2020 Sparse Coding with Gated Learned ISTA ICLR 2020 Stochastic Gradient Descent in Correlated Settings: A Study on Gaussian Processes NeurIPS 2020 Stochastic Hamiltonian Gradient Methods for Smooth Games ICML 2020 Stochastic Optimization with Laggard Data Pipelines NeurIPS 2020 Structured Policy Iteration for Linear Quadratic Regulator ICML 2020 Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization NeurIPS 2020 Towards Understanding the Dynamics of the First-Order Adversaries ICML 2020 Training Linear Neural Networks: Non-Local Convergence and Complexity Results ICML 2020 Understanding Approximate Fisher Information for Fast Convergence of Natural Gradient Descent in Wide Neural Networks NeurIPS 2020 Understanding the Impact of Model Incoherence on Convergence of Incremental SGD with Random Reshuffle ICML 2020 Zap Q-Learning With Nonlinear Function Approximation NeurIPS 2020 A Convergence Analysis of Distributed SGD with Communication-Efficient Gradient Sparsification IJCAI 2019 AdaShift: Decorrelation and Convergence of Adaptive Learning Rate Methods ICLR 2019 Analysis of Quantized Models ICLR 2019 A New Approach to Laplacian Solvers and Flow Problems JMLR 2019 An Improved Convergence Analysis of Stochastic Variance-Reduced Policy Gradient UAI 2019 A Solvable High-Dimensional Model of GAN NeurIPS 2019 A Sufficient Condition for Convergences of Adam and RMSProp CVPR 2019 Characterizing the Exact Behaviors of Temporal Difference Learning Algorithms Using Markov Jump Linear System Theory NeurIPS 2019 Communication trade-offs for Local-SGD with large step size NeurIPS 2019 Conditions on Features for Temporal Difference-Like Methods to Converge IJCAI 2019 Convergence Analysis of Gradient-Based Learning in Continuous Games UAI 2019