stochastic gradient descent

AdaScale SGD: A User-Friendly Algorithm for Distributed Training ICML 2020 A De Novo Divide-and-Merge Paradigm for Acoustic Model Optimization in Automatic Speech Recognition IJCAI 2020 A Double Residual Compression Algorithm for Efficient Distributed Learning AISTATS 2020 A General System of Differential Equations to Model First-Order Adaptive Algorithms JMLR 2020 A Lyapunov analysis for accelerated gradient methods: from deterministic to stochastic case AISTATS 2020 A Mean Field Analysis Of Deep ResNet And Beyond: Towards Provably Optimization Via Overparameterization From Depth ICML 2020 Anchor Box Optimization for Object Detection WACV 2020 An Empirical Study of Stochastic Gradient Descent with Structured Covariance Noise AISTATS 2020 An Exponential Learning Rate Schedule for Deep Learning ICLR 2020 An Implicit Form of Krasulina's k-PCA Update without the Orthonormality Constraint AAAI 2020 An Improved Analysis of Stochastic Gradient Descent with Momentum NeurIPS 2020 A Rule for Gradient Estimator Selection, with an Application to Variational Inference AISTATS 2020 Asymptotic Analysis via Stochastic Differential Equations of Gradient Descent Algorithms in Statistical and Computational Paradigms JMLR 2020 Asymptotics of Wide Networks from Feynman Diagrams ICLR 2020 A Theoretical and Practical Framework for Regression and Classification from Truncated Samples AISTATS 2020 A Tight Convergence Analysis for Stochastic Gradient Descent with Delayed Updates ALT 2020 At Stability's Edge: How to Adjust Hyperparameters to Preserve Minima Selection in Asynchronous Training of Neural Networks? ICLR 2020 Auditing Differentially Private Machine Learning: How Private is Private SGD? NeurIPS 2020 Augment Your Batch: Improving Generalization Through Instance Repetition CVPR 2020 A Unified Framework of Online Learning Algorithms for Training Recurrent Neural Networks JMLR 2020 A Unified q-Memorization Framework for Asynchronous Stochastic Optimization JMLR 2020 A Unified Theory of SGD: Variance Reduction, Sampling, Quantization and Coordinate Descent AISTATS 2020 Auto-Tuning Structured Light by Optical Stochastic Gradient Descent CVPR 2020 Bad Global Minima Exist and SGD Can Reach Them NeurIPS 2020 Bayesian filtering unifies adaptive and non-adaptive neural network optimization methods NeurIPS 2020