Moreover, through further merging a graph learning term, this shared coefficient matrix can simultaneously capture the global and local information among multiple views and few learned view-specific anchors for
However, it used the k-means to find anchors multiple times, and the running time on large-scale datasets is still very long. Sun et al. [40] combined anchor learning and graph construction into a unified optimization framework to improve the quality of selected anchors, and the time ...
Seurat13 parameters were obtained from online tutorials:63 The dataset was normalised, scaled, and dimensionally reduced using Seurat based on highly variable genes selected by JOINTLY. Integration anchors were identified using reciprocal PCA and highly variable genes selected by JOINTLY. The datasets wer...
Scal- able multi-view subspace clustering with unified anchors. In ACMMM, page 3528–3536, 2021. 1, 5, 6 [28] Grigorios Tzortzis and Aristidis Likas. Kernel-based weighted multi-view clustering. In 2012 IEEE 12th Inter- national Conference on Data Mining, pages 675–684, 2012. 1 [29] ...
However, misidentification of anchors from different batches might have led to reduced accuracy for the α and β cells’ classification. Fig. 4: Clustering results for the pancreatic islet data generated from different scRNA-seq protocols. a The t-SNE plots in which cells were colored by batch...
Among them, investigating the relation- ships between multiple objects is a crucial topic [5, 21, 22], especially for multi-view learning, which holds for anchor- based multi-view clustering[7, 44]. Some existing methods delve into the consistency of views by...
DeepImpute is an ensemble method consisting of multiple autoencoder-like deep neural networks, where each network is trained to learn the relationship between a set of input genes and a set of target genes. Input and target gene sets are selected based on correlation of gene expression values. ...
ensuring stable anchor selection results, and they possess the capability to better characterize the intrinsic structure of the data. Additionally, when dealing with citation networks [117], biochemical graphs [118] or social networks [119], ALG can acquire anchors based on given similarity graphs....
Third, although our method is anchor-based, it significantly outperforms most competitors, indicating that using a small number of anchors selected by DAS in MCHBG, instead of the entire data point cloud can provide enough effective clustering information. Additionally, in terms of CPU running time...
In recent years, combining multiple sources or views of datasets for data clustering has been a popular practice for improving clustering accuracy. As different views are different representations of the same set of instances, we can simultaneously use information from multiple views to improve the cl...