Our method sets different values of the weight-decay coefficients layer by layer so that the ratio of the scale of back-propagated gradients and that of the weight decay is constant throughout the network. By utilizing such a setting, we can avoid under or over-fitting and train all layers...
Thus, we set the weight decay strength to 0 in all our experiments. Increasing model sparsity rate using a cubic schedule throughout the pruning pipeline also turned out to improve accuracy for most models compared to the constant sparsity baseline (Table ...
We show that this discriminative dimensionality reduction can be done by 1x1 Convolution, Batch Normalization, and Weight Decay in one CNN, which we refer to as Neural Discriminative Dimensionality Reduction (NDDR). We perform ablation analysis in details for different configurations in training the ...
(0.9,0.98)"--lr 0.0005\--lr-scheduler inverse_sqrt --stop-min-lr 1e-09 --warmup-updates 10000 --warmup-init-lr 1e-07 --apply-bert-init --weight-decay 0.01 \ --fp16 --clip-norm 2.0 --max-update 300000 --task translation_glat --criterion glat_loss --arch glat_sd --noise ...
Rather than suppling a scalar learning rate and weight decay to the optimization function, supply the following vectors: locallearningRates,weightDecays=module:getOptimConfig(baseLearningRate,baseWeightDecay) The SGD config table should then be of the form: ...
In this paper, we propose layer-wise weight decay for efficient training of deep neural networks. Our method sets different values of the weight-decay coefficients layer by layer so that the ratio of...doi:10.1007/978-3-319-75786-5_23Masato Ishii...
Free-edge stress fields are of an utmost localized nature exhibiting steep stress gradients and they rapidly decay with increasing distance from the laminates' edges. Layer-wise theory has already been used to analyse the stress field at the free edges of the laminates. In this investigation, ...
The decay of the signal in the near UV and the beginning of the visible light spectrum, when the skin darkens, was expected and is the most obvious characteristic. Rather than simply diffusing, the LE becomes more absorbent with increasing pigmentation. The optical barrier of the epidermis (in...
Decoupled Weight Decay Regularization. International Conference on Learning Representations. 2019. Available online: https://openreview.net/forum?id=Bkg6RiCqY7 (accessed on 1 November 2022). Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those ...
The proposed model is trained for 300 epochs using AdamW optimizer [34] with weight decay 0.05, batch size 128 and peak learning rate 5 × 10−4−4. The number of linear warmup epochs is 20 with a cosine learning rate schedule. Meanwhile, typical schemes, including Mixup [35], ...