FedMM: Saddle Point Optimization for Federated Adversarial Domain Adaptation

Last update: Jun 29, 2022

Related tags

Overview

This repository contains the code accompanying the paper " FedMM: Saddle Point Optimization for Federated Adversarial Domain Adaptation" Paper link:

Requirements to run the code:

Python 3.7
Tensorflow 1.14.0
numpy 1.20.3
tqdm

Download dataset:

Download mnistm data:

curl -L -O http://www.eecs.berkeley.edu/Research/Projects/CS/vision/grouping/BSR/BSR_bsds500.tgz

Preprocess mnistm dataset

python create_mnistm.py

Experiments on Federated Domain Adaptation:

Usage for the Proposed FedMM on DANN loss:

python train.py -max_iter=15000 -lambda1_decay=1.05 -adv_loss='DANN'

Usage for the Proposed FedMM on MDD loss:

python train.py -max_iter=50000 -lambda1_decay=1.01 -adv_loss='MDD'

Usage for the Proposed FedMM on CDAN loss

python train.py -max_iter=30000 -lambda1_decay=1.02 -adv_loss='CDAN'

Reference

@misc{2110.08477,
Author = {Yan Shen and Jian Du and Hao Zhang and Benyu Zhang and Zhanghexuan Ji and Mingchen Gao},
Title = {FedMM: Saddle Point Optimization for Federated Adversarial Domain Adaptation},
Year = {2021},
Eprint = {arXiv:2110.08477},
}

FedMM: Saddle Point Optimization for Federated Adversarial Domain Adaptation

Related tags

Overview

Requirements to run the code:

Download dataset:

Experiments on Federated Domain Adaptation:

Reference

Owner

Mesh Graphormer is a new transformer-based method for human pose and mesh reconsruction from an input image

PyTorch implementation of 'Gen-LaneNet: a generalized and scalable approach for 3D lane detection'

Here I will explain the flow to deploy your custom deep learning models on Ultra96V2.

🤗 Transformers: State-of-the-art Natural Language Processing for Pytorch, TensorFlow, and JAX.

Weakly Supervised Segmentation with Tensorflow. Implements instance segmentation as described in Simple Does It: Weakly Supervised Instance and Semantic Segmentation, by Khoreva et al. (CVPR 2017).

DCA - Official Python implementation of Delaunay Component Analysis algorithm

Notebooks, slides and dataset of the CorrelAid Machine Learning Winter School

Code implementing "Improving Deep Learning Interpretability by Saliency Guided Training"

Simple PyTorch implementations of Badnets on MNIST and CIFAR10.

Awesome AI Learning with +100 AI Cheat-Sheets, Free online Books, Top Courses, Best Videos and Lectures, Papers, Tutorials, +99 Researchers, Premium Websites, +121 Datasets, Conferences, Frameworks, Tools

Python SDK for building, training, and deploying ML models

Weakly-Supervised Semantic Segmentation Network with Deep Seeded Region Growing (CVPR 2018).

Official TensorFlow code for the forthcoming paper

A simple, unofficial implementation of MAE using pytorch-lightning

Data & Code for ACCENTOR Adding Chit-Chat to Enhance Task-Oriented Dialogues

MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.

AI pipelines for Nvidia Jetson Platform

OpenLT: An open-source project for long-tail classification

These are the materials for the paper "Few-Shot Out-of-Domain Transfer Learning of Natural Language Explanations"

Label Mask for Multi-label Classification