Search Results for author: Jiankun Shi

Found 1 papers, 0 papers with code

AnchorGAE: General Data Clustering via $O(n)$ Bipartite Graph Convolution

no code implementations12 Nov 2021 Hongyuan Zhang, Jiankun Shi, Rui Zhang, Xuelong Li

The core problems mainly come from two aspects: (1) the graph is unavailable in the most clustering scenes so that how to construct high-quality graphs on the non-graph data is usually the most important part; (2) given n samples, the graph-based clustering methods usually consume at least $\mathcal O(n^2)$ time to build graphs and the graph convolution requires nearly $\mathcal O(n^2)$ for a dense graph and $\mathcal O(|\mathcal{E}|)$ for a sparse one with $|\mathcal{E}|$ edges.

Clustering

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