TCT
by yaodongyu
TCT: Convexifying Federated Learning using Bootstrapped Neural Tangent Kernels
AI summary
Optimization framework
An approach to train and optimize machine learning models in a decentralized setting by convexifying the optimization process
- stars
- 4
- forks
- 3
- watching
- 6
Similar projects
Found by comparing what the projects do, not just their names.
Optimization framework
This project presents optimization techniques for federated learning and minimax games in the context of machine learning
Optimization framework
A software framework for training neural networks to optimize dielectric metasurfaces using physics-driven generative models and global optimization algorithms.
Federated Learning Framework
A framework for federated learning that leverages the neural tangent kernel to address statistical heterogeneity in distributed machine learning.
Optimization algorithm
An optimizer that automatically tunes momentum and learning rate using local quadratic approximation.
Federated learning optimization
An approach to efficient federated learning by progressively training models on client devices with reduced communication and computation requirements.
Optimization framework
A framework for optimizing hyperparameters in machine learning models using Bayesian optimization
Decentralized optimizer
A modular JAX implementation of federated learning via posterior averaging for decentralized optimization
Hyperparameter optimizer
A reinforcement learning-based framework for optimizing hyperparameters in distributed machine learning environments.
Optimization framework
A collection of numerical experiments and code for demonstrating the performance of decentralized nonconvex optimization methods
Topology optimizer
Optimization code for topology optimization problems using machine learning and deep learning techniques
Federated Learning Algorithm
An implementation of a federated learning algorithm for training Graph Convolutional Networks on semi-supervised node classification tasks.
Model Training Framework
A framework for collaborative machine learning model training that leverages similarity between model representations to correct local training.
Federated learner optimizer
A tool for training federated learning models with adaptive gradient balancing to handle class imbalance in multi-client scenarios.
Optimization framework
A library for solving large-scale optimization problems with flexible and scalable vector and operator definitions
Federated Learning Framework
Develops a framework to balance competing goals in federated learning by decoupling generic and personalized prediction tasks.
