Federated multi-armed bandits(FMAB)是新的bandit范式,主要灵感来源于cognitive radio 和recommender systems的实际应用场景。这篇论文提出了一个通用型FMAB框架,并研究了该框架下的两种模型。 首先研究了近似模型,在该近似模型中,不同的local model都是global model 的服从于一个未知分布的随机实现。在这个近似模型中,...
Each client is associated with a multi-armed bandit in which each arm yields i.i.d. rewards following a Gaussian distribution with an unknown mean and known variance. The set of arms is assumed to be the same at all the clients. We define two notions of best arm local and global. The...
Aggregation Emerging Trends in Federated Learning: From Model Fusion to Federated X Learning Incentive A Comprehensive Survey of Incentive Mechanism for Federated Learning A Survey of Incentive Mechanism Design for Federated Learning Incentive Mechanisms for Federated Learning: From Economic and Game Theoretic...
the multi-armed bandit (Yoshida et al.2020) method was used to reduce the exploration and the exploitation and trade off in the mobile network. This method helps manage uncertainty caused by a huge amount of data, and one of the main advantages ...
We consider a $K$ -armed bandit problem in general graphs where agents are arbitrarily connected and each of them has limited memorizing capabilities and ... F Li,X Yuan,LX Cheng - IEEE/ACM Transactions on Networking: A Joint Publication of the IEEE Communications Soceity, the IEEE Computer ...
Based on this fact, in this paper, we design a multi-armed-bandit (MAB)-based edge scheduling scheme to improve the training efficiency and reduce the latency for FL within IoV. Particularly, considering a high requirement of security for IoV related wireless services, we further design the ...
FeDXL: Provable Federated Learning for Deep X-Risk Optimization [pdf] [code] FedBR: Improving Federated Learning on Heterogeneous Data via Local Learning Bias Reduction [pdf] [code] One-Shot Federated Conformal Prediction [pdf] [code] Revisiting Weighted Aggregation in Federated Learning with Neural...
Automated Collaborator Selection for Federated Learning with Multi-Armed Bandit Agents. In Proceedings of the 4th FlexNets Workshop on Flexible Networks Artificial Intelligence Supported Network Flexibility and Agility, Virtual Event, 23 August 2021. [Google Scholar] [CrossRef] Ji, S.; Pan, S.; ...
4. Multi-Armed Bandit (MAB) for Optimal MPTCP Scheduling In this section, we first provide a short background of MAB and then employ MAB to model and solve the scheduling problem (11). Next, we improve MAB’s efficiency with federated learning and opportunistic scheduling. MAB employs a seq...
4. Multi-Armed Bandit (MAB) for Optimal MPTCP Scheduling In this section, we first provide a short background of MAB and then employ MAB to model and solve the scheduling problem (11). Next, we improve MAB’s efficiency with federated learning and opportunistic scheduling. MAB employs a seq...