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2205.14840
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Maximizing Global Model Appeal in Federated Learning

v1v2 (latest)

Maximizing Global Model Appeal in Federated Learning

30 May 2022

Divyansh Jhunjhunwala

ArXiv (abs)PDF HTML

Papers citing "Maximizing Global Model Appeal in Federated Learning"

4 / 4 papers shown

CoRAG: Collaborative Retrieval-Augmented Generation

CoRAG: Collaborative Retrieval-Augmented GenerationNorth American Chapter of the Association for Computational Linguistics (NAACL), 2025

200

0

0

02 Apr 2025

CYCle: Choosing Your Collaborators Wisely to Enhance Collaborative Fairness in Decentralized Learning

CYCle: Choosing Your Collaborators Wisely to Enhance Collaborative Fairness in Decentralized Learning

Samuel Horváth

Karthik Nandakumar

402

2

0

21 Jan 2025

Rethinking the Starting Point: Collaborative Pre-Training for Federated
Downstream Tasks

Rethinking the Starting Point: Collaborative Pre-Training for Federated Downstream Tasks

Yun-Wei Chu

Seyyedali Hosseinalipour

Christopher G. Brinton

310

1

0

03 Feb 2024

Incentivizing Honesty among Competitors in Collaborative Learning and Optimization

Incentivizing Honesty among Competitors in Collaborative Learning and OptimizationNeural Information Processing Systems (NeurIPS), 2023

Florian E. Dorner

Nikola Konstantinov

Georgi Pashaliev

Martin Vechev

446

10

0

25 May 2023