Mathematics & Optimization

Statistically Preconditioned Accelerated Gradient Method for Distributed Optimization ICML 2020 Statistical Optimal Transport posed as Learning Kernel Embedding NeurIPS 2020 Statistical Testing on ASR Performance via Blockwise Bootstrap Interspeech 2020 Stein Self-Repulsive Dynamics: Benefits From Past Samples NeurIPS 2020 Stochastically Dominant Distributional Reinforcement Learning ICML 2020 Stochastic Approximate Gradient Descent via the Langevin Algorithm AAAI 2020 Stochastic bandits with arm-dependent delays ICML 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 Frank-Wolfe for Constrained Finite-Sum Minimization ICML 2020 Stochastic Gauss-Newton Algorithms for Nonconvex Compositional Optimization ICML 2020 Stochastic Gradient and Langevin Processes ICML 2020 Stochastic Hamiltonian Gradient Methods for Smooth Games ICML 2020 Stochasticity of Deterministic Gradient Descent: Large Learning Rate for Multiscale Objective Function NeurIPS 2020 Stochastic Online Learning with Probabilistic Graph Feedback AAAI 2020 Stochastic Optimization for Non-convex Inf-Projection Problems ICML 2020 Stochastic Optimization with Heavy-Tailed Noise via Accelerated Gradient Clipping NeurIPS 2020 Stochastic Optimization with Laggard Data Pipelines NeurIPS 2020 StochasticRank: Global Optimization of Scale-Free Discrete Functions ICML 2020 Stochastic Recursive Variance-Reduced Cubic Regularization Methods AISTATS 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 Strategic Campaign Management in Apportionment Elections IJCAI 2020 Strategies for Cooperative UAVs Using Model Predictive Control IJCAI 2020