#计算机科学#Polynomial Learning Rate Decay Scheduler for PyTorch
Pytorch cyclic cosine decay learning rate scheduler
#计算机科学#Gradually-Warmup Learning Rate Scheduler for PyTorch
Cyclic learning rate TensorFlow implementation.
It contains Data Augmentaion, Strided convolution, Batch Normalization, Leaky Relu, Global Average pooling, L2 Regularization, learning rate decay, He initialization, Tensorboard, Save, Restore
Transfer Learning using state-of-the-art CNN architectures (ResNet34 and Xception). Class engineering, learning rate/weight decay tuning and one-cycle policy are implemented.
PyTorch learning rate scheduler CosineAnnealingWarmRestarts with initial linear warmup for n steps followed by wight decay in consecutive cycles
Decoupled Weight Decay Regularization (ICLR 2019)
On the Variance of the Adaptive Learning Rate and Beyond
Adaptive and Momental Bounds for Adaptive Learning Rate Methods.
Python Implementation of Decay Replay Mining (DREAM)
PyTorch optimizers with sparse momentum and weight decay
Deep Learning 中文翻译
Sample code for learning redux with hooks by creating an exchange rate calculator
#学习与技能提升#《MIT Deep Learning》PDF格式
ASP.NET Core rate limiting middleware
Rate limiter middleware
Simple Tensorflow implementation of "Adaptive Gradient Methods with Dynamic Bound of Learning Rate" (ICLR 2019)
Basic rate-limiting middleware for the Express web server