stochastic gradient descent

Global Convergence of Stochastic Gradient Descent for Some Non-convex Matrix Problems ICML 2015 Hilbert maps: scalable continuous occupancy mapping with stochastic gradient descent RSS 2015 Learning from Data with Heterogeneous Noise using SGD AISTATS 2015 Learning with Incremental Iterative Regularization NeurIPS 2015 Marginalizing Stacked Linear Denoising Autoencoders JMLR 2015 Online Tensor Methods for Learning Latent Variable Models JMLR 2015 On Variance Reduction in Stochastic Gradient Descent and its Asynchronous Variants NeurIPS 2015 Open Problem: The landscape of the loss surfaces of multilayer networks COLT 2015 Path-SGD: Path-Normalized Optimization in Deep Neural Networks NeurIPS 2015 Probabilistic Line Searches for Stochastic Optimization NeurIPS 2015 SGD Algorithms based on Incomplete U-statistics: Large-Scale Minimization of Empirical Risk NeurIPS 2015 Stochastic Spectral Descent for Restricted Boltzmann Machines AISTATS 2015 Surrogate Functions for Maximizing Precision at the Top ICML 2015 Taming the Wild: A Unified Analysis of Hogwild-Style Algorithms NeurIPS 2015 Top Rank Supervised Binary Coding for Visual Search ICCV 2015 Variance Reduced Stochastic Gradient Descent with Neighbors NeurIPS 2015 A Bayesian Framework for Online Classifier Ensemble ICML 2014 Accelerated Stochastic Gradient Method for Composite Regularization AISTATS 2014 Adaptivity of Averaged Stochastic Gradient Descent to Local Strong Convexity for Logistic Regression JMLR 2014 Bayesian Sampling Using Stochastic Gradient Thermostats NeurIPS 2014 Communication-Efficient Distributed Dual Coordinate Ascent NeurIPS 2014 Doubly Aggressive Selective Sampling Algorithms for Classification AISTATS 2014 Efficient Low-Rank Stochastic Gradient Descent Methods for Solving Semidefinite Programs AISTATS 2014 Fast large-scale optimization by unifying stochastic gradient and quasi-Newton methods ICML 2014 Large-Margin Convex Polytope Machine NeurIPS 2014