Implementation of the federated dual coordinate descent (FedDCD) method.

Related tags

Deep LearningFedDCD.jl
Overview

FedDCD.jl

Implementation of the federated dual coordinate descent (FedDCD) method.

Installation

To install, just call

Pkg.add("https://github.com/ZhenanFanUBC/FedDCD.jl.git")

Get data

We get data from the website of LIBSVM. To download the datasets, just call

mkdir data
cd ./data
wget https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/binary/rcv1_train.binary.bz2
wget https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/binary/rcv1_test.binary.bz2
wget https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/multiclass/mnist.scale.bz2
wget https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/multiclass/mnist.scale.t.bz2
bzip2 -d rcv1_train.binary.bz2
bzip2 -d rcv1_test.binary.bz2
bzip2 -d mnist.scale.bz2
bzip2 -d mnist.scale.t.bz2

Run FedAvg for toy example.

include("experiments/PrimalMethods.jl")
RunFedAvgAndProx(
    "data/rcv1_train.binary",
    "data/rcv1_train.binary"
    1e-2,
    0.0,
    0.3,
    0.1,
    100,
    "results/toy.txt"
    )

Run FedDCD for toy example.

include("experiments/DualMethods.jl")
RunFedDCD(
    "data/rcv1_train.binary",
    "data/rcv1_train.binary"
    1e-2,
    0.3,
    0.1,
    100,
    "results/toy.txt"
    )

Citing this package

If you use FedDCD.jl for published work, we encourage you to cite the software.

Use the following BibTeX citation:

@article{fan2022dual,
      title={A dual approach for federated learning}, 
      author={Zhenan Fan and Huang Fang and Michael P. Friedlander},
      year={2022},
      eprint={2201.11183},
      archivePrefix={arXiv},
      primaryClass={cs.LG}
}

Credits

FedDCD.jl is developed by Zhenan Fan and Huang Fang

Owner
Zhenan Fan
I am a Ph.D. student in the Department of Computer Science at the University of British Columbia. You can find more about me from https://zhenanf.me.
Zhenan Fan
GitHub Repository
2021-AIAC-QQ-Browser-Hyperparameter-Optimization-Rank6

2021-AIAC-QQ-Browser-Hyperparameter-Optimization-Rank6

Aigege 8 Mar 31, 2022
Edge-aware Guidance Fusion Network for RGB-Thermal Scene Parsing

EGFNet Edge-aware Guidance Fusion Network for RGB-Thermal Scene Parsing Dataset and Results Test maps: 百度网盘 提取码：zust Citation @ARTICLE{ author={Zhou,

ShaohuaDong 10 Dec 08, 2022
Single Image Super-Resolution (SISR) with SRResNet, EDSR and SRGAN

Single Image Super-Resolution (SISR) with SRResNet, EDSR and SRGAN Introduction Image super-resolution (SR) is the process of recovering high-resoluti

8 Apr 15, 2022
Data and extra materials for the food safety publications classifier

Data and extra materials for the food safety publications classifier The subdirectories contain detailed descriptions of their contents in the README.

1 Jan 20, 2022
以孤立语假设和宽度优先搜索为基础，构建了一种多通道堆叠注意力Transformer结构的斗地主ai

ddz-ai 介绍 斗地主是一种扑克游戏。游戏最少由3个玩家进行，用一副54张牌（连鬼牌），其中一方为地主，其余两家为另一方，双方对战，先出完牌的一方获胜。 ddz-ai以孤立语假设和宽度优先搜索为基础，构建了一种多通道堆叠注意力Transformer结构的系统，使其经过大量训练后，能在实际游戏中获

freefuiiismyname 88 May 15, 2022
LF-YOLO (Lighter and Faster YOLO) is used to detect defect of X-ray weld image.

This project is based on ultralytics/yolov3. LF-YOLO (Lighter and Faster YOLO) is used to detect defect of X-ray weld image. Download $ git clone http

26 Dec 13, 2022
IhoneyBakFileScan Modify - 批量网站备份文件扫描器，增加文件规则，优化内存占用

ihoneyBakFileScan_Modify 批量网站备份文件泄露扫描工具 2022.2.8 添加、修改内容 增加备份文件fuzz规则 修改备份文件大小判断

VMsec 220 Jan 05, 2023
The implementation our EMNLP 2021 paper "Enhanced Language Representation with Label Knowledge for Span Extraction".

LEAR The implementation our EMNLP 2021 paper "Enhanced Language Representation with Label Knowledge for Span Extraction". See below for an overview of

杨攀 93 Jan 07, 2023
Fuzzer for Linux Kernel Drivers

difuze: Fuzzer for Linux Kernel Drivers This repo contains all the sources (including setup scripts), you need to get difuze up and running. Tested on

seclab 344 Dec 27, 2022
Official implementation of NeuralFusion: Online Depth Map Fusion in Latent Space

NeuralFusion This is the official implementation of NeuralFusion: Online Depth Map Fusion in Latent Space. We provide code to train the proposed pipel

53 Jan 01, 2023
PyTorch implementation of ENet

PyTorch-ENet PyTorch (v1.1.0) implementation of ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation, ported from the lua-torc

David Silva 333 Dec 29, 2022
Source code for From Stars to Subgraphs

GNNAsKernel Official code for From Stars to Subgraphs: Uplifting Any GNN with Local Structure Awareness Visualizations GNN-AK(+) GNN-AK(+) with Subgra

44 Dec 19, 2022
This repository contains the source code for the paper "DONeRF: Towards Real-Time Rendering of Compact Neural Radiance Fields using Depth Oracle Networks",

DONeRF: Towards Real-Time Rendering of Compact Neural Radiance Fields using Depth Oracle Networks Project Page | Video | Presentation | Paper | Data L

Facebook Research 281 Dec 22, 2022
Image restoration with neural networks but without learning.

Warning! The optimization may not converge on some GPUs. We've personally experienced issues on Tesla V100 and P40 GPUs. When running the code, make s

Dmitry Ulyanov 7.4k Jan 01, 2023
Code and data of the ACL 2021 paper: Few-Shot Text Ranking with Meta Adapted Synthetic Weak Supervision

MetaAdaptRank This repository provides the implementation of meta-learning to reweight synthetic weak supervision data described in the paper Few-Shot

THUNLP 5 Jun 16, 2022
Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit

CNTK Chat Windows build status Linux build status The Microsoft Cognitive Toolkit (https://cntk.ai) is a unified deep learning toolkit that describes

Microsoft 17.3k Dec 29, 2022
Stacked Generative Adversarial Networks

Stacked Generative Adversarial Networks This repository contains code for the paper "Stacked Generative Adversarial Networks", CVPR 2017. Part of the

Xun Huang 241 May 07, 2022
Official implementation for: Blended Diffusion for Text-driven Editing of Natural Images.

Blended Diffusion for Text-driven Editing of Natural Images Blended Diffusion for Text-driven Editing of Natural Images Omri Avrahami, Dani Lischinski

328 Dec 30, 2022
Official Repsoitory for "Mish: A Self Regularized Non-Monotonic Neural Activation Function" [BMVC 2020]

Mish: Self Regularized Non-Monotonic Activation Function BMVC 2020 (Official Paper) Notes: (Click to expand) A considerably faster version based on CU

Xa9aX ツ 1.2k Dec 29, 2022
Dataset Condensation with Contrastive Signals

Dataset Condensation with Contrastive Signals This repository is the official implementation of Dataset Condensation with Contrastive Signals (DCC). T

3 May 19, 2022