Efficient Federated Incomplete Multi-View Clustering
Authors: Suyuan Liu, Hao Yu, Hao Tan, Ke Liang, Siwei Wang, Shengju Yu, En Zhu, Xinwang Liu
ICML 2025 | Venue PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Extensive experiments on benchmark datasets demonstrate the superiority of EFIMVC in clustering accuracy, communication efficiency, and privacy preservation. Our code is publicly available at https://github.com/Tracesource/EFIMVC. ... We conduct experiments on seven multi-view datasets: Protein Fold, Web KB, 100Leaves, CCV, YTF10, CIFAR10, and MNIST, with detailed descriptions provided in Table 1. |
| Researcher Affiliation | Academia | 1College of Computer Science and Technology, National University of Defence Technology, Changsha, China 2Academy of Military Sciences, Beijing, China. Correspondence to: Xinwang Liu <EMAIL>. |
| Pseudocode | Yes | Algorithm 1 The proposed EFIMVC |
| Open Source Code | Yes | Our code is publicly available at https://github.com/Tracesource/EFIMVC. |
| Open Datasets | Yes | We conduct experiments on seven multi-view datasets: Protein Fold, Web KB, 100Leaves, CCV, YTF10, CIFAR10, and MNIST, with detailed descriptions provided in Table 1. ... 1http://mkl.ucsd.edu/dataset/protein-fold-prediction/ 2http://www.cs.umd.edu/sen/lbc-proj/LBC.html 3https://www.archive.ics.uci.edu/dataset/241 4https://www.ee.columbia.edu/ln/dvmm/CCV/ 5https://www.micc.unifi.it/resources/datasets/e-ytf/ 6http://www.cs.toronto.edu/kriz/cifar.html 7http://yann.lecun.com/exdb/mnist/ |
| Dataset Splits | No | Following the definition in (Wang et al., 2022), we generate nine versions of each dataset with missing rates increasing in 10% increments, ensuring that no sample is entirely missing from all views. ... Additionally, for methods that obtain final results through k-means, we repeat the clustering process 20 times and report the average performance to mitigate the impact of initialization randomness. |
| Hardware Specification | Yes | All experiments are conducted on a computer with Intel Core i9-10900X CPU and 64G RAM. |
| Software Dependencies | No | Eq. (10) is a standard quadratic programming problem, which we solve using existing software packages. ... Similarly, we solve Eq. (14) with the quadratic programming package. |
| Experiment Setup | Yes | EFIMVC has two hyperparameters, λ and β, with search ranges of [0.001, 0.1, 1, 100]. ... The parameter settings in EFIMVC are grid search. For both λ and β, we search them in [0.001, 0.1, 1, 100]. ... for federated multi-view clustering algorithms that cannot handle missing views, we fill the missing entries with zeros before inputting the data. Additionally, for methods that obtain final results through k-means, we repeat the clustering process 20 times and report the average performance to mitigate the impact of initialization randomness. |