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.

10papers

Papers

February 20, 2025

VFL-RPS: Relevant Participant Selection in Vertical Federated Learning
Afsana Khan, Marijn ten Thij, Guangzhi Tang, Anna Wilbik
Maastricht University●TilburgUniversity
Vertical Federated Learning Participant Selection Horizontal Federated Learning Participant State

December 17, 2024

Concurrent vertical and horizontal federated learning with fuzzy cognitive maps
Jose L Salmeron, Irina Arévalo
Fuzzy Cognitive Map Diverse Datasets Federated Setting Learning Framework Cognitive Map Horizontal Federated Learning

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
Vertical Federated Learning Backdoor Defense Backdoor Attack VFL Algorithm Horizontal Federated Learning Person Identification

June 25, 2024

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

May 24, 2024

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

April 22, 2024

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

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
Horizontal Federated Learning Partitioned Data Stochastic Gradient Descent Mobile Health Vertical Pole Vertical 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 Intel Xeon Recommendation System Deep Learning Recommendation Model Horizontal Federated Learning Training Data Secure Approach

March 4, 2022

Continual Horizontal Federated Learning for Heterogeneous Data
Junki Mori, Isamu Teranishi, Ryo Furukawa
Local Learning Machine Learning Heterogeneous Data Continual 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
Horizontal Federated Learning Auction Based Online Service Incentive Mechanism Budget Constraint

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
Horizontal Federated Learning Client Contribution Centralized Machine Learning Auction Based Federated Training

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
Horizontal Federated Learning Vertical Federated Learning Global Scale Global Information Traffic Flow Prediction

Horizontal Federated Learning

Papers

VFL-RPS: Relevant Participant Selection in Vertical Federated Learning

Concurrent vertical and horizontal federated learning with fuzzy cognitive maps

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