stochastic gradient descent

Solving Ridge Regression using Sketched Preconditioned SVRG ICML 2016 Starting Small - Learning with Adaptive Sample Sizes ICML 2016 Stochastic Gradient Methods for Distributionally Robust Optimization with f-divergences NeurIPS 2016 Stochastic Multiple Choice Learning for Training Diverse Deep Ensembles NeurIPS 2016 Stochastic Optimization for Large-scale Optimal Transport NeurIPS 2016 Stochastic Optimization for Multiview Representation Learning using Partial Least Squares ICML 2016 Stochastic Variance Reduction for Nonconvex Optimization ICML 2016 Towards Stability and Optimality in Stochastic Gradient Descent AISTATS 2016 Train faster, generalize better: Stability of stochastic gradient descent ICML 2016 Unbounded Bayesian Optimization via Regularization AISTATS 2016 Variance Reduction for Faster Non-Convex Optimization ICML 2016 Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks NeurIPS 2016 Yggdrasil: An Optimized System for Training Deep Decision Trees at Scale NeurIPS 2016 Adaptive Hashing for Fast Similarity Search ICCV 2015 A Stochastic PCA and SVD Algorithm with an Exponential Convergence Rate ICML 2015 Asynchronous Parallel Stochastic Gradient for Nonconvex Optimization NeurIPS 2015 Asynchronous stochastic convex optimization: the noise is in the noise and SGD don't care NeurIPS 2015 Averaged Least-Mean-Squares: Bias-Variance Trade-offs and Optimal Sampling Distributions AISTATS 2015 Beyond Convexity: Stochastic Quasi-Convex Optimization NeurIPS 2015 Color Constancy by Learning to Predict Chromaticity from Luminance NeurIPS 2015 Deep learning with Elastic Averaging SGD NeurIPS 2015 Efficient Non-greedy Optimization of Decision Trees NeurIPS 2015 Equilibrated adaptive learning rates for non-convex optimization NeurIPS 2015 Escaping From Saddle Points — Online Stochastic Gradient for Tensor Decomposition COLT 2015 Finite-Time Analysis of Projected Langevin Monte Carlo NeurIPS 2015