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TIFF: Tokenized Incentive for Federated Learning
Jingoo Han
, Ahmad Faraz Khan
, Syed Zawad
,
Ali Anwar
, Nathalie Baracaldo Angel
, Yi Zhou
, Feng Yan
, Ali R. Butt
Computer Science and Engineering
Research output
:
Chapter in Book/Report/Conference proceeding
›
Conference contribution
12
Scopus citations
Overview
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Keyphrases
Federated Learning
100%
Token-based
100%
Token
50%
Model Accuracy
20%
Learning Process
20%
Incentive Mechanism
20%
High Performance
10%
Measure Data
10%
Performance Model
10%
Training Model
10%
Data Quality
10%
Reduction Rate
10%
Training Time
10%
Client Needs
10%
Final Model
10%
Privacy Concerns
10%
Machine Learning Models
10%
Self-interest
10%
Overfitting
10%
Self-other
10%
Learning Model
10%
Local Data
10%
Improvement Factor
10%
Long-term Engagement
10%
High-quality Data
10%
Improving Model
10%
Learning Scenario
10%
Random Exploration
10%
Delay in Payment
10%
Reasonable Compensation
10%
Historical Accuracy
10%
Large Amount of Data
10%
Security Concerns
10%
High Utility Patterns
10%
Local Datasets
10%
Utility Improvement
10%
Computer Science
Federated machine learning
100%
Model Accuracy
20%
Learning Process
20%
Incentive Mechanism
20%
Performance Model
10%
Privacy Concern
10%
Security Concern
10%
Machine Learning Model
10%