Synthetic dataset for personalized federated unsupervised learning

doi:doi:10.57702/chpocxdu

Synthetic dataset for personalized federated unsupervised learning

The dataset used in the paper is a synthetic dataset for personalized federated unsupervised learning. It is generated by sampling a global PC, V ∗ ∈ St(d, r), uniformly on the Steifel manifold. The dataset is used to evaluate the performance of the proposed algorithms for personalized adaptive dimensionality reduction and personalized federated diffusion models.

BibTex:

@dataset{Kaan_Ozkara_and_Bruce_Huang_and_Ruida_Zhou_and_Suhas_Diggavi_2024,
    abstract = {The dataset used in the paper is a synthetic dataset for personalized federated unsupervised learning. It is generated by sampling a global PC, V ∗ ∈ St(d, r), uniformly on the Steifel manifold. The dataset is used to evaluate the performance of the proposed algorithms for personalized adaptive dimensionality reduction and personalized federated diffusion models.},
    author = {Kaan Ozkara and Bruce Huang and Ruida Zhou and Suhas Diggavi},
    doi = {10.57702/chpocxdu},
    institution = {No Organization},
    keyword = {'Diffusion Models', 'Dimensionality Reduction', 'Personalized Federated Unsupervised Learning', 'Synthetic Dataset'},
    month = {dec},
    publisher = {TIB},
    title = {Synthetic dataset for personalized federated unsupervised learning},
    url = {https://service.tib.eu/ldmservice/dataset/synthetic-dataset-for-personalized-federated-unsupervised-learning},
    year = {2024}
}