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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

Practical and Private (Deep) Learning Without Sampling or Shuffling ICML 2021
Byzantine-Resilient High-Dimensional SGD with Local Iterations on Heterogeneous Data ICML 2021
A Gradient Based Strategy for Hamiltonian Monte Carlo Hyperparameter Optimization ICML 2021
Loss Surface Simplexes for Mode Connecting Volumes and Fast Ensembling ICML 2021
Adaptive Knowledge Driven Regularization for Deep Neural Networks AAAI 2021
SGD: The Role of Implicit Regularization, Batch-size and Multiple-epochs NIPS 2021
On the Power of Differentiable Learning versus PAC and SQ Learning NIPS 2021
Communication-efficient SGD: From Local SGD to One-Shot Averaging NIPS 2021
When All We Need is a Piece of the Pie: A Generic Framework for Optimizing Two-way Partial AUC ICML 2021
When Are Solutions Connected in Deep Networks? NIPS 2021
The Implicit Bias of Minima Stability: A View from Function Space NIPS 2021
Large-Scale Wasserstein Gradient Flows NIPS 2021
Batch Normalization Orthogonalizes Representations in Deep Random Networks NIPS 2021
Why Lottery Ticket Wins? A Theoretical Perspective of Sample Complexity on Sparse Neural Networks NIPS 2021
Faster Neural Network Training with Approximate Tensor Operations NIPS 2021
Towards Understanding Learning in Neural Networks with Linear Teachers ICML 2021
Online stochastic gradient descent on non-convex losses from high-dimensional inference JMLR 2021
Moshpit SGD: Communication-Efficient Decentralized Training on Heterogeneous Unreliable Devices NIPS 2021
Error Compensated Distributed SGD Can Be Accelerated NIPS 2021
Efficient Generalization with Distributionally Robust Learning NIPS 2021
Last iterate convergence of SGD for Least-Squares in the Interpolation regime. NIPS 2021
Enabling Fast Differentially Private SGD via Just-in-Time Compilation and Vectorization NIPS 2021
Generalization Guarantee of SGD for Pairwise Learning NIPS 2021
Gradient Methods Never Overfit On Separable Data JMLR 2021
Simple Stochastic and Online Gradient Descent Algorithms for Pairwise Learning NIPS 2021