convergence guarantee

Controlling Neural Networks via Energy Dissipation ICCV 2019 Convergence Guarantees for a Class of Non-convex and Non-smooth Optimization Problems JMLR 2019 Convergence Guarantees for Adaptive Bayesian Quadrature Methods NeurIPS 2019 Distributional reinforcement learning with linear function approximation AISTATS 2019 Efficient Dictionary Learning with Gradient Descent ICML 2019 GAN-Based Projector for Faster Recovery With Convergence Guarantees in Linear Inverse Problems ICCV 2019 Learning Neural PDE Solvers with Convergence Guarantees ICLR 2019 Modeling simple structures and geometry for better stochastic optimization algorithms AISTATS 2019 Multi-Order Information for Working Set Selection of Sequential Minimal Optimization AISTATS 2019 On Fast Convergence of Proximal Algorithms for SQRT-Lasso Optimization: Don’t Worry About its Nonsmooth Loss Function UAI 2019 Poisson-Minibatching for Gibbs Sampling with Convergence Rate Guarantees NeurIPS 2019 SySCD: A System-Aware Parallel Coordinate Descent Algorithm NeurIPS 2019 The Role of Memory in Stochastic Optimization UAI 2019 An Analysis of Categorical Distributional Reinforcement Learning AISTATS 2018 An Off-policy Policy Gradient Theorem Using Emphatic Weightings NeurIPS 2018 Convergence guarantees for a class of non-convex and non-smooth optimization problems ICML 2018 Convergent Tree Backup and Retrace with Function Approximation ICML 2018 Decoupled Parallel Backpropagation with Convergence Guarantee ICML 2018 Goal-HSVI: Heuristic Search Value Iteration for Goal POMDPs IJCAI 2018 Langevin Monte Carlo and JKO splitting COLT 2018 Let’s be Honest: An Optimal No-Regret Framework for Zero-Sum Games ICML 2018 On Markov Chain Gradient Descent NeurIPS 2018 On Q-learning Convergence for Non-Markov Decision Processes IJCAI 2018 On the Convergence and Robustness of Training GANs with Regularized Optimal Transport NeurIPS 2018 SBEED: Convergent Reinforcement Learning with Nonlinear Function Approximation ICML 2018