Meanwhile, SGD performs poorly compared to SGD with Momentum when the learning rate is large When the batch size is small, the optimal learn- ing rates for
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[PDF] Control Batch Size and Learning Rate to Generalize Well - NeurIPS
Each point represents a model Totally 1,600 points are plotted has a positive correlation with the ratio of batch size to learning rate, which suggests a negative correlation between the generalization ability of neural networks and the ratio This result builds the theoretical foundation of the training strategy
[PDF] Which Algorithmic Choices Matter at Which Batch Sizes? - NIPS
studied how various heuristics for adjusting the learning rate as a function of batch size affect the relationship between batch size and training time Shallue et al
[PDF] Towards Explaining the Regularization Effect of Initial Large
Abstract Stochastic gradient descent with a large initial learning rate is widely used for the connection between large batch size and small learning rate 3
[PDF] On the Generalization Benefit of Noise in Stochastic Gradient Descent
learning rate and batch size (Krizhevsky, 2014; Goyal et al , 2017; Smith et al , that SGD with Momentum significantly outperforms vanilla SGD (Sutskever et The primary difference between convergence bounds and the SDE perspective
[PDF] On the Generalization Benefit of Noise in Stochastic Gradient Descent
Meanwhile, SGD performs poorly compared to SGD with Momentum when the learning rate is large When the batch size is small, the optimal learn- ing rates for
[PDF] Train Deep Neural Networks with Small Batch Sizes - IJCAI
Deep learning architectures are usually proposed with millions of as vanilla SGD even with small batch size Our difference between noisy and noiseless gradient However, it attains a better convergence rate when batch size is con-
[PDF] Why Does Large Batch Training Result in Poor - HUSCAP
ponents of machine learning because a better solution generally leads to a more accurate problems In section 4, we explain why the training with a large batch size in This relationship is not so simple in neural networks because the loss learning rate during training can be useful for accelerating the training In
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