FedAEB: Deep Reinforcement Learning Based Joint Client Selection and Resource Allocation Strategy for Heterogeneous Federated Learning

Research article (IEEE Transactions on Vehicular Technology, 2024) · cited 32× · AI/ML
Press Enter · cited answer in seconds

FedAEB: Deep Reinforcement Learning Based Joint Client Selection and Resource Allocation Strategy for Heterogeneous Federated Learning

Summary

FedAEB: Deep Reinforcement Learning Based Joint Client Selection and Resource Allocation Strategy for Heterogeneous Federated Learning is a scholarly article[1].

Key Facts

  • FedAEB: Deep Reinforcement Learning Based Joint Client Selection and Resource Allocation Strategy for Heterogeneous Federated Learning's instance of is recorded as scholarly article[2].

📑 Cite this page

Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.

APA 4ort.xyz Knowledge Graph. (2026). FedAEB: Deep Reinforcement Learning Based Joint Client Selection and Resource Allocation Strategy for Heterogeneous Federated Learning. Retrieved May 24, 2026, from https://4ort.xyz/entity/fedaeb-deep-reinforcement-learning-based-joint-client-selection-and-resource-allocation-strategy-for-heterogeneous-feder
MLA “FedAEB: Deep Reinforcement Learning Based Joint Client Selection and Resource Allocation Strategy for Heterogeneous Federated Learning.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/fedaeb-deep-reinforcement-learning-based-joint-client-selection-and-resource-allocation-strategy-for-heterogeneous-feder.
BibTeX @misc{4ortxyz_fedaeb-deep-reinforcement-learning-based-joint-client-selection-and-resource-allocation-strategy-for-heterogeneous-feder_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{FedAEB: Deep Reinforcement Learning Based Joint Client Selection and Resource Allocation Strategy for Heterogeneous Federated Learning}}, year = {2026}, url = {https://4ort.xyz/entity/fedaeb-deep-reinforcement-learning-based-joint-client-selection-and-resource-allocation-strategy-for-heterogeneous-feder}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): FedAEB: Deep Reinforcement Learning Based Joint Client Selection and Resource Allocation Strategy for Heterogeneous Federated Learning — https://4ort.xyz/entity/fedaeb-deep-reinforcement-learning-based-joint-client-selection-and-resource-allocation-strategy-for-heterogeneous-feder (retrieved 2026-05-24)

Canonical URL: https://4ort.xyz/entity/fedaeb-deep-reinforcement-learning-based-joint-client-selection-and-resource-allocation-strategy-for-heterogeneous-feder · Last refreshed: