Incentive mechanism in federated learning
WebMoreover, we propose an effective incentive mechanism combining reputation with contract theory to motivate high-reputation mobile devices with high-quality data to participate in … WebAs the initial variant of federated learning (FL), horizontal federated learning (HFL) applies to the situations where datasets share the same feature space but differ in the sample …
Incentive mechanism in federated learning
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WebMar 3, 2024 · A Survey of Incentive Mechanism Design for Federated Learning Abstract: Federated learning is promising in enabling large-scale machine learning by massive … WebEnsuring fairness in incentive mechanisms for federated learning (FL) is essential to attracting high-quality clients and building a sustainable FL ecosystem. Most existing …
WebMar 3, 2024 · As compared to the current incentive mechanism design in other fields, such as crowdsourcing, cloud computing, smart grid, etc., the incentive mechanism for federated learning is more challenging ... WebNov 20, 2024 · Incentive Mechanisms for Federated Learning: From Economic and Game Theoretic Perspective Xuezhen Tu, Kun Zhu, Nguyen Cong Luong, Dusit Niyato, Yang …
WebIncentive Mechanism Incentive mechanisms have been studied in other areas such as crowdsensing (Gong and Shroff 2024; Yang et al. 2012), but these works have not been directly applied to FL area (Deng et al. 2024). Game theory and auction can be used as approaches to provide incentives for FL (Khan et al. 2024; Zhan et al. 2024). Web[10] Zhan Y, Zhang J, Hong Z, et al. A survey of incentive mechanism design for federated learning[J]. IEEE Transactions on Emerging Topics in Computing, 2024. ... Zeng R, Zeng C, …
WebApr 9, 2024 · However, the challenges such as incentive mechanisms for participating in training and worker (i.e., mobile devices) selection schemes for reliable federated learning, have not been explored yet.
WebMar 8, 2024 · Request PDF An Incentive Mechanism for Federated Learning in Wireless Cellular Networks: An Auction Approach Federated Learning (FL) is a distributed learning framework that can deal with the ... state of flow meaningWebIn order to effectively solve these problems, we propose FIFL, a fair incentive mechanism for federated learning. FIFL rewards workers fairly to attract reliable and efficient ones while punishing and eliminating the malicious ones based on a dynamic real-time worker assessment mechanism. state of flow csikszentmihalyiWebJun 8, 2024 · Federated learning (FL) is an emerging paradigm for machine learning, in which data owners can collaboratively train a model by sharing gradients instead of their raw data. Two fundamental research problems in FL are incentive mechanism and privacy protection. The former focuses on how to incentivize data owners to participate in FL. state of flow definitionWebJan 28, 2024 · Federated Learning Incentive Mechanism Design via Enhanced Shapley Value Method Federated learning (FL) is an emerging collaborative machine learning … state of flux incWebMay 1, 2024 · An incentive mechanism is urgently required in order to encourage high-quality workers to participate in FL and to punish the attackers. In this paper, we propose FGFL, a blockchain-based incentive governor for Federated Learning. In FGFL, we assess the participants with reputation and contribution indicators. state of flux songWebDec 4, 2024 · Download Citation On Dec 4, 2024, Jingyuan Liu and others published Incentive Mechanism Design For Federated Learning in Multi-access Edge Computing Find, read and cite all the research you ... state of flux release dateWebthe PAs an incentive for participating in code development and enforcement activities, Massachusetts needed to develop a mechanism for measuring the impact of these … state of flux company