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Found 4 papers, 1 papers with code
Fair Concurrent Training of Multiple Models in Federated Learning
We show how our fairness-based learning and incentive mechanisms impact training convergence and finally evaluate our algorithm with multiple sets of learning tasks on real world datasets.
An LLM-Based Digital Twin for Optimizing Human-in-the Loop Systems
In this paper, we present a case study that employs LLM agents to mimic the behaviors and thermal preferences of various population groups (e. g. young families, the elderly) in a shopping mall.
Differentially Private Deep Q-Learning for Pattern Privacy Preservation in MEC Offloading
Mobile edge computing (MEC) is a promising paradigm to meet the quality of service (QoS) requirements of latency-sensitive IoT applications.
FIRE: A Failure-Adaptive Reinforcement Learning Framework for Edge Computing Migrations
In edge computing, users' service profiles are migrated due to user mobility.
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