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stochastic gradient descent

1088 papers

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Also known as

SGD

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

Orthogonalized SGD and Nested Architectures for Anytime Neural Networks ICML 2020
Understanding the Impact of Model Incoherence on Convergence of Incremental SGD with Random Reshuffle ICML 2020
Is Local SGD Better than Minibatch SGD? ICML 2020
Infinity Learning: Learning Markov Chains from Aggregate Steady-State Observations AAAI 2020
Local Regularizer Improves Generalization AAAI 2020
Optimization Methods for Interpretable Differentiable Decision Trees Applied to Reinforcement Learning AISTATS 2020
An Empirical Study of Stochastic Gradient Descent with Structured Covariance Noise AISTATS 2020
Training Neural Networks for and by Interpolation ICML 2020
Stochastic Gradient and Langevin Processes ICML 2020
Growing Adaptive Multi-hyperplane Machines ICML 2020
The Complexity of Finding Stationary Points with Stochastic Gradient Descent ICML 2020
SGD Learns One-Layer Networks in WGANs ICML 2020
Fine-Grained Analysis of Stability and Generalization for Stochastic Gradient Descent ICML 2020
Extrapolation for Large-batch Training in Deep Learning ICML 2020
Coresets for Data-efficient Training of Machine Learning Models ICML 2020
The Impact of Neural Network Overparameterization on Gradient Confusion and Stochastic Gradient Descent ICML 2020
Landscape Connectivity and Dropout Stability of SGD Solutions for Over-parameterized Neural Networks ICML 2020
Fractional Underdamped Langevin Dynamics: Retargeting SGD with Momentum under Heavy-Tailed Gradient Noise ICML 2020
On the Generalization Benefit of Noise in Stochastic Gradient Descent ICML 2020
The Implicit and Explicit Regularization Effects of Dropout ICML 2020
Scalable Differential Privacy with Certified Robustness in Adversarial Learning ICML 2020
Stochastic Approximate Gradient Descent via the Langevin Algorithm AAAI 2020
Inefficiency of K-FAC for Large Batch Size Training AAAI 2020
Temporal Network Embedding with High-Order Nonlinear Information AAAI 2020
Augment Your Batch: Improving Generalization Through Instance Repetition CVPR 2020