stochastic optimization

Safe Linear Stochastic Bandits AAAI 2020 Sample Efficient Policy Gradient Methods with Recursive Variance Reduction ICLR 2020 SCAFFOLD: Stochastic Controlled Averaging for Federated Learning ICML 2020 Scalable Variational Bayesian Kernel Selection for Sparse Gaussian Process Regression AAAI 2020 Second-Order Information in Non-Convex Stochastic Optimization: Power and Limitations COLT 2020 SPAN: A Stochastic Projected Approximate Newton Method AAAI 2020 Stage-wise Conservative Linear Bandits NeurIPS 2020 Stochastic Approximate Gradient Descent via the Langevin Algorithm AAAI 2020 Stochastic AUC Maximization with Deep Neural Networks ICLR 2020 Stochastic Conditional Gradient Methods: From Convex Minimization to Submodular Maximization JMLR 2020 Stochastic Coordinate Minimization with Progressive Precision for Stochastic Convex Optimization ICML 2020 Stochastic Flows and Geometric Optimization on the Orthogonal Group ICML 2020 Stochastic Gauss-Newton Algorithms for Nonconvex Compositional Optimization ICML 2020 Stochastic Hamiltonian Gradient Methods for Smooth Games ICML 2020 Stochastic Loss Function AAAI 2020 Stochastic Optimization for Non-convex Inf-Projection Problems ICML 2020 Stochastic Optimization for Performative Prediction NeurIPS 2020 Stochastic Optimization with Heavy-Tailed Noise via Accelerated Gradient Clipping NeurIPS 2020 Stochastic Optimization with Laggard Data Pipelines NeurIPS 2020 Stochastic Stein Discrepancies NeurIPS 2020 Stochastic Subspace Cubic Newton Method ICML 2020 Stochastic Variance-Reduced Algorithms for PCA with Arbitrary Mini-Batch Sizes AISTATS 2020 Stochastic Variational Inference for Dynamic Correlated Topic Models UAI 2020 Temporal Variability in Implicit Online Learning NeurIPS 2020 The Blind Men and the Elephant: Integrated Offline/Online Optimization Under Uncertainty IJCAI 2020