Stochastic gradient descent with a large initial learning rate is widely used for training large batch size or small learning rate results in sharp local minima
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[PDF] Control Batch Size and Learning Rate to Generalize Well - NeurIPS
When employing SGD to train deep neural networks, we should control the batch size not too large and learning rate not too small, in order to make the networks
[PDF] Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour
To achieve this result, we adopt a linear scal- ing rule for adjusting learning rates as a function of mini- batch size and develop a new warmup scheme that over-
[PDF] Which Algorithmic Choices Matter at Which Batch Sizes? - NIPS
much larger critical batch sizes than stochastic gradient descent with optimal learning rates and large batch training, making it a useful tool to generate
[PDF] Towards Explaining the Regularization Effect of Initial Large
Stochastic gradient descent with a large initial learning rate is widely used for training large batch size or small learning rate results in sharp local minima
[PDF] Why Does Large Batch Training Result in Poor - HUSCAP
In section 4, we explain why the training with a large batch size in neural networks learning rate during training can be useful for accelerating the training In
[PDF] Large Batch Optimization for Deep Learning - UC Berkeley EECS
21 jui 2019 · One important rule is to increase the LR (learning rate) by √ b when batch size is scaled by b since the variance of the gradient estimation
[PDF] Large Batch Optimization for Object Detection: Training COCO in 12
A rule of thumb for training neural network is the Linear Scaling Rule (LSR) [10], which sug- gests that when the batch size becomes K times, the learning rate
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