We propose a novel approach called Graph-structured Plug & Play Federated Learning (FedPnP) with proven convergence to improve the performance of local models trained in the Personalized Federated Learning (PFL)
self.old_to_new.update({o: n.item()})returnself.old_to_newclassMeanSplitAgglomerative(Split):""" split labels associated with a node to x branches by the mean vector of each class. close classes should be grouped together :param labels: numpy array of the labels :param branches: the n...
1 先瞄Title -- “PERSONALIZED FEDERATED LEARNING WITH FEATURE ALIGNMENT AND CLASSIFIER COLLABORATION” 1.1 Personalized FL 意味着客户端与服务端的模型参数会有所不同。 1.2 Feature Alignment 特征对齐这个词本身有点抽象,在不同子领域里面各有不同的理解。 1.3 Classifier Collaboration 分类器合作,意味着作者...
当以“federated personal”为关键词,在 dblp 上进行文献检索的时候,会发现个性化联邦学习(PFL, Personalized Federated Learning)的研究在2021年的有明显增加。 经小鱼的查询,至22年4月16日针对个性化联邦学习的综述文章仅两篇[1][2],其中...
For simplicity and to include mainstream per- sonalized federated learning techniques, we adopt the basic sharing backbone and personalize head method in the fol- lowing statements. Furthermore, we discuss the compatibil- ity of FedAS with other personalized parameter partitioni...
paper链接:Towards Personalized Federated Learning | IEEE Journals & Magazine | IEEE Xplore 正文: 这篇文章回顾了联邦学习Federated Learning的提出FedAvg,然后指出FedAvg在noniid的数据下,会发生client drift的问题,也就是global model会因为每个client的heterogenous data问题,造成global model的收敛点与local model的收...
learning rate of the server inner_lr: float, learning rate of the node embed_lr: float, learning rate of the embedding layer wd: float, weight decay of the server inner_wd: float, weight decay of the node embed_dim: int, the dimension of the embedding layer output hyper_hid: int, th...
Publication There is a growing interest in applying machine learning techniques to healthcare. Recently, federated learning (FL) isgaining popularity since it allows researchers to train powerful models without compromising data privacy and security. However, theperformance of exis...
PyTorch Implementation of Personalized federated learning with theoretical guarantees: A model-agnostic meta-learning approach pytorchmeta-learningfederated-learningpersonalized-federated-learning UpdatedFeb 1, 2023 Python omarfoq/knn-per Star43 Code
当以“federated personal”为关键词,在 dblp 上进行文献检索的时候,会发现个性化联邦学习(PFL, Personalized Federated Learning)的研究在2021年的有明显增加。 经小鱼的查询,至22年4月16日针对个性化联邦学习的综述文章仅两篇[1][2],其中写得比较全面的一篇已被IEEE Transactions on Neural Networks and Learning ...