A Principled Approach to Data Valuation for Federated Learning
Authors:
- 26 November 2020
- book chapter
- Published by Springer Nature
- p. 153-167
Abstract
No abstract availableKeywords
All Related Versions
This publication has 13 references indexed in Scilit:
- Incentive Mechanism for Reliable Federated Learning: A Joint Optimization Approach to Combining Reputation and Contract TheoryIEEE Internet of Things Journal, 2019
- Incentive Design for Efficient Federated Learning in Mobile Networks: A Contract Theory Approach2019
- Efficient task-specific data valuation for nearest neighbor algorithmsProceedings of the VLDB Endowment, 2019
- Federated Learning for Keyword Spotting2019
- BadNets: Evaluating Backdooring Attacks on Deep Neural NetworksIEEE Access, 2019
- A cooperative game-theoretic approach to quantify the value of personal data in networks2017
- Query-Based Data PricingJournal of the ACM, 2015
- Sell your experiences: a market mechanism based incentive for participatory sensing2010
- Dynamic Resource Pricing on Federated Clouds2010
- On the Complexity of Cooperative Solution ConceptsMathematics of Operations Research, 1994