Optimization

Stability and Generalization of Learning Algorithms that Converge to Global Optima ICML 2018 Stabilizing Adversarial Nets with Prediction Methods ICLR 2018 Stateless Datacenter Load-balancing with Beamer NSDI 2018 State-of-the-art Chinese Word Segmentation with Bi-LSTMs EMNLP 2018 Statistical and Computational Trade-Offs in Kernel K-Means NeurIPS 2018 Statistical mechanics of low-rank tensor decomposition NeurIPS 2018 Statistical Sparse Online Regression: A Diffusion Approximation Perspective AISTATS 2018 Stein Variational Gradient Descent Without Gradient ICML 2018 Stochastic algorithms for entropy-regularized optimal transport problems AISTATS 2018 Stochastic Anytime Search for Bounding Marginal MAP IJCAI 2018 Stochastic Chebyshev Gradient Descent for Spectral Optimization 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 Nested Variance Reduction for Nonconvex Optimization NeurIPS 2018 Stochastic PCA with ℓ_2 and ℓ_1 Regularization ICML 2018 Stochastic Proximal Algorithms for AUC Maximization ICML 2018 Stochastic Second-Order Method for Large-Scale Nonconvex Sparse Learning Models IJCAI 2018 Stochastic Spectral and Conjugate Descent Methods NeurIPS 2018 Stochastic Three-Composite Convex Minimization with a Linear Operator AISTATS 2018 Stochastic Training of Graph Convolutional Networks with Variance Reduction ICML 2018 Stochastic Variance-Reduced Cubic Regularized Newton Methods ICML 2018 Stochastic Variance-Reduced Policy Gradient ICML 2018 Streamlining Variational Inference for Constraint Satisfaction Problems NeurIPS 2018