The is the official implementation of ICML 2023 paper "Revisiting Weighted Aggregation in Federated Learning with Neural Networks".
-
Updated
Aug 28, 2023 - Python
#
weight-decay
Here are 8 public repositories matching this topic...
[NeurIPS 2023] The PyTorch Implementation of Scheduled (Stable) Weight Decay.
-
Updated
Feb 3, 2024 - Python
Investigating the Role of Weight Decay in Enhancing Nonconvex SGD, CVPR 2025
-
Updated
Jun 9, 2025 - Python
Advanced CIFAR-10 image classification using ResNet-inspired CNN with residual blocks, achieving 92%+ accuracy through comprehensive regularization, data augmentation, and professional ML engineering practices.
computer-vision deep-learning scikit-learn jupyter-notebook cnn pytorch seaborn dropout batch-normalization image-classification matplotlib resnet regularization cifar10 data-augmentation model-evaluation interpretability weight-decay train-validation-test
-
Updated
May 28, 2025 - Jupyter Notebook
Implementation of some new techniques from fastai and other papers which works with keras models
-
Updated
Dec 26, 2018 - Python
Super-Convergence on CIFAR10
sophia cifar10 lion second-order-optimization adamw super-convergence weight-decay sharpness-aware-minimization madgrad large-batch-optimization lion-optimizer
-
Updated
Jun 17, 2024 - Python
Folder contains implementation of Multi layer feed forward networks, Autoencoders, Sparse Autoencoders and many..
neural-network mnist autoencoder feedforward-neural-network regularization momentum backpropagation sparse-autoencoders sparse-autoencoder autoencoder-mnist weight-decay
-
Updated
May 17, 2019 - HTML
Machine Learning university project
-
Updated
Apr 1, 2019 - Python
Improve this page
Add a description, image, and links to the weight-decay topic page so that developers can more easily learn about it.
Add this topic to your repo
To associate your repository with the weight-decay topic, visit your repo's landing page and select "manage topics."