stochastic gradient descent

Federated Accelerated Stochastic Gradient Descent NeurIPS 2020 FetchSGD: Communication-Efficient Federated Learning with Sketching ICML 2020 Fine-Grained Analysis of Stability and Generalization for Stochastic Gradient Descent ICML 2020 FNNC: Achieving Fairness through Neural Networks IJCAI 2020 Fractional Underdamped Langevin Dynamics: Retargeting SGD with Momentum under Heavy-Tailed Gradient Noise ICML 2020 Gap-Aware Mitigation of Gradient Staleness ICLR 2020 GCN meets GPU: Decoupling “When to Sample” from “How to Sample” NeurIPS 2020 Gradient descent algorithms for Bures-Wasserstein barycenters COLT 2020 Gradient Perturbation is Underrated for Differentially Private Convex Optimization IJCAI 2020 Graph-Dependent Implicit Regularisation for Distributed Stochastic Subgradient Descent JMLR 2020 Growing Adaptive Multi-hyperplane Machines ICML 2020 Hausdorff Dimension, Heavy Tails, and Generalization in Neural Networks NeurIPS 2020 How Good is SGD with Random Shuffling? COLT 2020 How Good is the Bayes Posterior in Deep Neural Networks Really? ICML 2020 Implicit regularization for deep neural networks driven by an Ornstein-Uhlenbeck like process COLT 2020 Improved Analysis of Clipping Algorithms for Non-convex Optimization NeurIPS 2020 Improving Neural Network Training in Low Dimensional Random Bases NeurIPS 2020 Inefficiency of K-FAC for Large Batch Size Training AAAI 2020 Infinity Learning: Learning Markov Chains from Aggregate Steady-State Observations AAAI 2020 Is Local SGD Better than Minibatch SGD? ICML 2020 Landscape Connectivity and Dropout Stability of SGD Solutions for Over-parameterized Neural Networks ICML 2020 Learning Efficient Parameter Server Synchronization Policies for Distributed SGD ICLR 2020 Learning Halfspaces with Massart Noise Under Structured Distributions COLT 2020 Learning Polynomials in Few Relevant Dimensions COLT 2020 Learning Rate Adaptation for Differentially Private Learning AISTATS 2020