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联邦学习在ICLR 2023会议中的论文清单 [1]如下: A Statistical Framework for Personalized Federated Learning and Estimation: Theory, Algorithms, and Privacy作者 Kaan Ozkara 作者 Antonious M. Girgis 作…
参与方们的数据的特征空间和样本空间也许不是完全相同的,所以我们可以基于数据在不同参与方(parties)的特征空间和样本 ID 空间上的分布情况,将联邦学习分为水平联邦学习(horizontal federated learing)、垂直联邦学习(vertical federated learning)和联邦迁移学习(federated transfer learning)。 水平联邦学习(horizontal feder...
Overall, this survey can be a valuable resource for researchers who are interested in the emerging field of PFL as well as its potential for personalized machine learning in a federated environment. 展开 关键词: Personalized federated learning Model optimization Distributed machine learning Collaborative...
Zhang, Michael, et al. "Personalized federated learning with first order model optimization." arXiv preprint arXiv:2012.08565 (2020). 本文是一篇2021年发表在ICRL上的关于个性化联邦学习的文章,该文章赋予了客户一个新的角色,并提出一种新的权重策略,构造了一种在隐私和性能之间进行权衡的名为Fedfomo...
Such a training process does not compromise privacy and security, and each party can participate in and facilitate the optimization of the AI model and share the final model, without having to disclose raw data. As an active explorer and participant in federated lea...
So, the question is left open. Is there a chance for companies to create an efficient machine learning model while keeping all things on-device? In short, yes. Federated learning is here for those reasons. Federated machine learning approach ...
Federated Learning has sparked increasing interest as a promising approach to utilize large amounts of data stored on network edge devices. Federated Averaging is the most widely accepted Federated Learning framework. In Federated Averaging, the server keeps waiting for client models to compute the glo...
Communication costs(通信成本):通过设置了在联邦学习训练轮次期间选择客户端更新的预定义规则,有助于通过消除贡献最少的联邦学习客户端更新来最小化通信成本(论文链接:Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge)。 联邦蒸馏(Federated Distillation, FD)和联合增强(Federated Augm...
Industry-Scale Orchestrated Federated Learning for Drug Discovery Poisoning with Cerberus: Stealthy and Colluded Backdoor Attack against Federated Learning Echo of Neighbors: Privacy Amplification for Personalized Private Federated Learning with Shuffle Model Layer-Wise Adaptive Model Aggregation for Scalable Fed...