Horizontal Federated Learning

Horizontal Federated Learning (HFL) is a machine learning approach enabling collaborative model training across multiple devices without directly sharing their data. Current research emphasizes improving HFL efficiency through techniques like low-rank approximations and optimized communication strategies to reduce computational and communication costs, while also addressing vulnerabilities like backdoor attacks and developing incentive mechanisms to encourage participation. HFL's significance lies in its ability to train high-quality models on decentralized data while preserving privacy, with applications ranging from recommendation systems to e-health and wireless network optimization.

Papers

August 28, 2024

VFLIP: A Backdoor Defense for Vertical Federated Learning via Identification and Purification
Yungi Cho, Woorim Han, Miseon Yu, Younghan Lee, Ho Bae, Yunheung Paek
Backdoor Attack Person Identification Vertical Federated Learning Backdoor Defense VFL Algorithm Horizontal Federated Learning

June 25, 2024

Federated Dynamical Low-Rank Training with Global Loss Convergence Guarantees
Steffen Schotthöfer, M. Paul Laiu
Low Rank Splitting Algorithm Global Convergence Guarantee Horizontal Federated Learning

May 24, 2024

CAFe: Cost and Age aware Federated Learning
Sahan Liyanaarachchi, Kanchana Thilakarathna, Sennur Ulukus
Convergence Rate Hidden CoST Global Model Local Gradient Self Service CAFE Convergence Theory Horizontal Federated Learning Noisy Gradient

April 22, 2024

Mapping Wireless Networks into Digital Reality through Joint Vertical and Horizontal Learning
Zifan Zhang, Mingzhe Chen, Zhaohui Yang, Yuchen Liu
Digital Twin Wireless Network Horizontal Federated Learning 3D Joint Network Clustering

April 15, 2024

Communication-Efficient Hybrid Federated Learning for E-health with Horizontal and Vertical Data Partitioning
Chong Yu, Shuaiqi Shen, Shiqiang Wang, Kuan Zhang, Hai Zhao
Stochastic Gradient Descent Vertical Federated Learning Mobile Health Partitioned Data Vertical Pole Horizontal Federated Learning

July 11, 2022

Horizontal Federated Learning and Secure Distributed Training for Recommendation System with Intel SGX
Siyuan Hui, Yuqiu Zhang, Albert Hu, Edmund Song
Deep Learning Training Data Recommendation System Secure Approach Deep Learning Recommendation Model Horizontal Federated Learning Intel Xeon

March 4, 2022

Continual Horizontal Federated Learning for Heterogeneous Data
Junki Mori, Isamu Teranishi, Ryo Furukawa
Machine Learning Continual Learning Heterogeneous Data Local Learning Heterogeneous Input Horizontal Federated Learning

January 22, 2022

Online Auction-Based Incentive Mechanism Design for Horizontal Federated Learning with Budget Constraint
Jingwen Zhang, Yuezhou Wu, Rong Pan
Online Service Incentive Mechanism Budget Constraint Auction Based Horizontal Federated Learning

January 7, 2022

Auction-Based Ex-Post-Payment Incentive Mechanism Design for Horizontal Federated Learning with Reputation and Contribution Measurement
Jingwen Zhang, Yuezhou Wu, Rong Pan
Client Contribution Centralized Machine Learning Federated Training Auction Based Horizontal Federated Learning

December 2, 2021

How global observation works in Federated Learning: Integrating vertical training into Horizontal Federated Learning
Shuo Wan, Jiaxun Lu, Pingyi Fan, Yunfeng Shao, Chenghui Peng, Khaled B. Letaief
Vertical Federated Learning Traffic Flow Prediction Global Scale Global Information Horizontal Federated Learning

Horizontal Federated Learning

Papers

VFLIP: A Backdoor Defense for Vertical Federated Learning via Identification and Purification

Federated Dynamical Low-Rank Training with Global Loss Convergence Guarantees

CAFe: Cost and Age aware Federated Learning

Mapping Wireless Networks into Digital Reality through Joint Vertical and Horizontal Learning

Communication-Efficient Hybrid Federated Learning for E-health with Horizontal and Vertical Data Partitioning

Horizontal Federated Learning and Secure Distributed Training for Recommendation System with Intel SGX

Continual Horizontal Federated Learning for Heterogeneous Data

Online Auction-Based Incentive Mechanism Design for Horizontal Federated Learning with Budget Constraint

Auction-Based Ex-Post-Payment Incentive Mechanism Design for Horizontal Federated Learning with Reputation and Contribution Measurement

How global observation works in Federated Learning: Integrating vertical training into Horizontal Federated Learning