stochastic gradient descent

Assessing Generalization of SGD via Disagreement ICLR 2022 A Statistical Online Inference Approach in Averaged Stochastic Approximation NeurIPS 2022 Asymptotics of ℓ_2 Regularized Network Embeddings NeurIPS 2022 Asynchronous SGD Beats Minibatch SGD Under Arbitrary Delays NeurIPS 2022 A Unified Convergence Theorem for Stochastic Optimization Methods NeurIPS 2022 Automatic Learning of Subword Dependent Model Scales Interspeech 2022 Bayesian Neural Network Priors Revisited ICLR 2022 Benign Underfitting of Stochastic Gradient Descent NeurIPS 2022 Better Parameter-Free Stochastic Optimization with ODE Updates for Coin-Betting AAAI 2022 Better SGD using Second-order Momentum NeurIPS 2022 Black-Box Generalization: Stability of Zeroth-Order Learning NeurIPS 2022 Chaotic Dynamics are Intrinsic to Neural Network Training with SGD NeurIPS 2022 Clipped Stochastic Methods for Variational Inequalities with Heavy-Tailed Noise NeurIPS 2022 Communication-Compressed Adaptive Gradient Method for Distributed Nonconvex Optimization AISTATS 2022 Communication-efficient Distributed Learning for Large Batch Optimization ICML 2022 Conditionally Gaussian PAC-Bayes AISTATS 2022 Constrained Langevin Algorithms with L-mixing External Random Variables NeurIPS 2022 Continuous-Time Meta-Learning with Forward Mode Differentiation ICLR 2022 Convergence of online k-means AISTATS 2022 Convergence Rates of Non-Convex Stochastic Gradient Descent Under a Generic Lojasiewicz Condition and Local Smoothness ICML 2022 Data-Efficient Augmentation for Training Neural Networks NeurIPS 2022 Data sampling affects the complexity of online SGD over dependent data UAI 2022 Decomposable Non-Smooth Convex Optimization with Nearly-Linear Gradient Oracle Complexity NeurIPS 2022 Demystifying Why Local Aggregation Helps: Convergence Analysis of Hierarchical SGD AAAI 2022 Detached Error Feedback for Distributed SGD with Random Sparsification ICML 2022