"Simulations for the paper 'A Review Article On Gradient Descent Optimization Algorithms' by Sebastian Roeder"
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Updated
Jun 19, 2024 - Jupyter Notebook
"Simulations for the paper 'A Review Article On Gradient Descent Optimization Algorithms' by Sebastian Roeder"
Nadir: Cutting-edge PyTorch optimizers for simplicity & composability! 🔥🚀💻
Implementation and comparison of zero order vs first order method on the AdaMM (aka AMSGrad) optimizer: analysis of convergence rates and minima shape
The implementation of the algorithm shows that OPTIMISTIC-AMSGRAD improves AMSGRAD in terms of various measures: training loss, testing loss, and classification accuracy on training/testing data over epochs.
Deep Learning Optimizers
Quasi Hyperbolic Rectified DEMON Adam/Amsgrad with AdaMod, Gradient Centralization, Lookahead, iterative averaging and decorrelated Weight Decay
A Repository to Visualize the training of Linear Model by optimizers such as SGD, Adam, RMSProp, AdamW, ASMGrad etc
A comparison between implementations of different gradient-based optimization algorithms (Gradient Descent, Adam, Adamax, Nadam, Amsgrad). The comparison was made on some of the most common functions used for testing optimization algorithms.
The optimization methods in deep learning explained by Vietnamese such as gradient descent, momentum, NAG, AdaGrad, Adadelta, RMSProp, Adam, Adamax, Nadam, AMSGrad.
Custom Optimizer in TensorFlow(定义你自己的Tensorflow Optimizer)
Reproducing the paper "PADAM: Closing The Generalization Gap of Adaptive Gradient Methods In Training Deep Neural Networks" for the ICLR 2019 Reproducibility Challenge
[Python] [arXiv/cs] Paper "An Overview of Gradient Descent Optimization Algorithms" by Sebastian Ruder
Generalization of Adam, AdaMax, AMSGrad algorithms for PyTorch
Fully connected neural network for digit classification using MNIST data
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