stochastic optimization

On the Convergence of Adam and Beyond ICLR 2018 On the insufficiency of existing momentum schemes for Stochastic Optimization ICLR 2018 Profitable Bandits ACML 2018 Randomized Block Cubic Newton Method ICML 2018 SEGA: Variance Reduction via Gradient Sketching NeurIPS 2018 SGDLibrary: A MATLAB library for stochastic optimization algorithms JMLR 2018 Shampoo: Preconditioned Stochastic Tensor Optimization ICML 2018 SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path-Integrated Differential Estimator NeurIPS 2018 Stochastic Composite Mirror Descent: Optimal Bounds with High Probabilities NeurIPS 2018 Stochastic Cubic Regularization for Fast Nonconvex Optimization NeurIPS 2018 Stochastic Expectation Maximization with Variance Reduction NeurIPS 2018 Stochastic Fractional Hamiltonian Monte Carlo IJCAI 2018 Stochastic Primal-Dual Method for Empirical Risk Minimization with O(1) Per-Iteration Complexity NeurIPS 2018 Stochastic Proximal Algorithms for AUC Maximization ICML 2018 Stochastic Second-Order Method for Large-Scale Nonconvex Sparse Learning Models IJCAI 2018 Stochastic Shake-Shake Regularization for Affective Learning from Speech Interspeech 2018 Stochastic Spectral and Conjugate Descent Methods NeurIPS 2018 Stochastic Three-Composite Convex Minimization with a Linear Operator AISTATS 2018 Stochastic Variance-Reduced Cubic Regularized Newton Methods ICML 2018 Stochastic Variance-Reduced Policy Gradient ICML 2018 Third-order Smoothness Helps: Faster Stochastic Optimization Algorithms for Finding Local Minima NeurIPS 2018 UCBoost: A Boosting Approach to Tame Complexity and Optimality for Stochastic Bandits IJCAI 2018 Understanding Short-Horizon Bias in Stochastic Meta-Optimization ICLR 2018 Using Large Ensembles of Control Variates for Variational Inference NeurIPS 2018 Zeroth-order (Non)-Convex Stochastic Optimization via Conditional Gradient and Gradient Updates NeurIPS 2018