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stochastic gradient descent

1088 papers

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Also known as

SGD ASGD SAGA SGM SGDA PSGD SKGD

Co-occurring keywords

non-convex optimization (546) distributed learning (563) neural network optimization (1293) convergence rate (606) convex optimization (1320) neural network (6616) variance reduction (520) stochastic optimization (1060) convergence analysis (394) differential privacy (1010)

Papers

Privacy Amplification via Random Check-Ins NIPS 2020
Minibatch vs Local SGD for Heterogeneous Distributed Learning NIPS 2020
Can Implicit Bias Explain Generalization? Stochastic Convex Optimization as a Case Study NIPS 2020
Dynamical mean-field theory for stochastic gradient descent in Gaussian mixture classification NIPS 2020
Stochastic Optimization with Laggard Data Pipelines NIPS 2020
Truncated Linear Regression in High Dimensions NIPS 2020
A Bayesian Perspective on Training Speed and Model Selection NIPS 2020
Robust, Accurate Stochastic Optimization for Variational Inference NIPS 2020
Mix and Match: An Optimistic Tree-Search Approach for Learning Models from Mixture Distributions NIPS 2020
Escaping Saddle-Point Faster under Interpolation-like Conditions NIPS 2020
Learning with Optimized Random Features: Exponential Speedup by Quantum Machine Learning without Sparsity and Low-Rank Assumptions NIPS 2020
Adaptive Importance Sampling for Finite-Sum Optimization and Sampling with Decreasing Step-Sizes NIPS 2020
Random Reshuffling: Simple Analysis with Vast Improvements NIPS 2020
SGD with shuffling: optimal rates without component convexity and large epoch requirements NIPS 2020
Continuous Regularized Wasserstein Barycenters NIPS 2020
Non-Convex SGD Learns Halfspaces with Adversarial Label Noise NIPS 2020
On the universality of deep learning NIPS 2020
Federated Accelerated Stochastic Gradient Descent NIPS 2020
Estimating Training Data Influence by Tracing Gradient Descent NIPS 2020
Random Reshuffling is Not Always Better NIPS 2020
Least Squares Regression with Markovian Data: Fundamental Limits and Algorithms NIPS 2020
An Implicit Form of Krasulina's k-PCA Update without the Orthonormality Constraint AAAI 2020
Optimal Epoch Stochastic Gradient Descent Ascent Methods for Min-Max Optimization NIPS 2020
Predicting Training Time Without Training NIPS 2020
Understanding Gradient Clipping in Private SGD: A Geometric Perspective NIPS 2020