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Aug 18, 2019 · In this paper, we present a comprehensive study of 13 learning rate functions and their associated LR policies by examining their range parameters, step ...
Evaluated through extensive experiments, we attempt to demystify the tuning of LR policies by identifying good LR policies with effective LR value ranges and ...
Missing: Polices | Show results with:Polices
This paper proposes a set of metrics for evaluating and selecting LR policies, including the classification confidence, variance, cost, and robustness, ...
We propose a set of metrics for evaluating and selecting LR policies, including the classification confidence, variance, cost, and robustness, and implement ...
Missing: Polices | Show results with:Polices
Good learning rates can train deep learning models with high accuracy or reach accuracy thresholds fast with low training costs [52,16].
A set of metrics for evaluating and selecting LR policies are proposed, including the classification confidence, variance, cost, and robustness, ...
Wu, Yanzhao, Liu, Ling, Bae, Juhyun et al. (2019). Demystifying Learning Rate Policies for High Accuracy Training of Deep Neural Networks . Share this citation.
Missing: Polices | Show results with:Polices
Aug 18, 2019 · PDF | Learning Rate (LR) is an important hyper-parameter to tune for effective training of deep neural networks (DNNs).
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This article presents a systematic approach to selecting and composing an LR policy for effective DNN training to meet desired target accuracy and reduce ...
A learning rate benchmarking and recommending tool, which will help practitioners efficiently select and compose good learning rate policies.