stochastic gradient descent

On the Local Minima of the Empirical Risk NeurIPS 2018 On Truly Block Eigensolvers via Riemannian Optimization AISTATS 2018 Optimal Distributed Learning with Multi-pass Stochastic Gradient Methods ICML 2018 Parallelizing Stochastic Gradient Descent for Least Squares Regression: Mini-batching, Averaging, and Model Misspecification JMLR 2018 Parameters as interacting particles: long time convergence and asymptotic error scaling of neural networks NeurIPS 2018 Parsimonious Bayesian deep networks NeurIPS 2018 Pipe-SGD: A Decentralized Pipelined SGD Framework for Distributed Deep Net Training NeurIPS 2018 SADAGRAD: Strongly Adaptive Stochastic Gradient Methods ICML 2018 SGD and Hogwild! Convergence Without the Bounded Gradients Assumption ICML 2018 SGD Learns Over-parameterized Networks that Provably Generalize on Linearly Separable Data ICLR 2018 SGDLibrary: A MATLAB library for stochastic optimization algorithms JMLR 2018 Sliced Wasserstein Distance for Learning Gaussian Mixture Models CVPR 2018 Slow and Stale Gradients Can Win the Race: Error-Runtime Trade-offs in Distributed SGD AISTATS 2018 Sparsified SGD with Memory NeurIPS 2018 SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path-Integrated Differential Estimator NeurIPS 2018 Stability and Generalization of Learning Algorithms that Converge to Global Optima ICML 2018 Stabilizing Adversarial Nets with Prediction Methods ICLR 2018 Statistical Optimality of Stochastic Gradient Descent on Hard Learning Problems through Multiple Passes NeurIPS 2018 Statistical Sparse Online Regression: A Diffusion Approximation Perspective AISTATS 2018 Stochastic Chebyshev Gradient Descent for Spectral Optimization NeurIPS 2018 Stochastic Composite Mirror Descent: Optimal Bounds with High Probabilities NeurIPS 2018 Stochastic gradient descent performs variational inference, converges to limit cycles for deep networks ICLR 2018 Stochastic Nested Variance Reduction for Nonconvex Optimization NeurIPS 2018 Stochastic PCA with ℓ_2 and ℓ_1 Regularization ICML 2018 The Convergence of Sparsified Gradient Methods NeurIPS 2018