stochastic gradient descent

When Do Neural Networks Outperform Kernel Methods? NeurIPS 2020 Why are Adaptive Methods Good for Attention Models? NeurIPS 2020 Zeno++: Robust Fully Asynchronous SGD ICML 2020 Accelerated Linear Convergence of Stochastic Momentum Methods in Wasserstein Distances ICML 2019 A Convergence Theory for Deep Learning via Over-Parameterization ICML 2019 Active Mini-Batch Sampling Using Repulsive Point Processes AAAI 2019 Active Probabilistic Inference on Matrices for Pre-Conditioning in Stochastic Optimization AISTATS 2019 AdaGrad Stepsizes: Sharp Convergence Over Nonconvex Landscapes ICML 2019 A Latent Variational Framework for Stochastic Optimization NeurIPS 2019 A Local Block Coordinate Descent Algorithm for the CSC Model CVPR 2019 A Stochastic Composite Gradient Method with Incremental Variance Reduction NeurIPS 2019 A Sufficient Condition for Convergences of Adam and RMSProp CVPR 2019 Asymmetric Valleys: Beyond Sharp and Flat Local Minima NeurIPS 2019 Asynchronous Proximal Stochastic Gradient Algorithm for Composition Optimization Problems AAAI 2019 A Tail-Index Analysis of Stochastic Gradient Noise in Deep Neural Networks ICML 2019 A Universally Optimal Multistage Accelerated Stochastic Gradient Method NeurIPS 2019 AutoAssist: A Framework to Accelerate Training of Deep Neural Networks NeurIPS 2019 A Variational Inequality Perspective on Generative Adversarial Networks ICLR 2019 Beating SGD Saturation with Tail-Averaging and Minibatching NeurIPS 2019 Calibrated Stochastic Gradient Descent for Convolutional Neural Networks AAAI 2019 Can SGD Learn Recurrent Neural Networks with Provable Generalization? NeurIPS 2019 Cascaded Projection: End-To-End Network Compression and Acceleration CVPR 2019 Characterization of Convex Objective Functions and Optimal Expected Convergence Rates for SGD ICML 2019 Cogra: Concept-Drift-Aware Stochastic Gradient Descent for Time-Series Forecasting AAAI 2019 Combining Global Sparse Gradients with Local Gradients in Distributed Neural Network Training EMNLP 2019