| Publisher | Microsoft | ||
|---|---|---|---|
| Format | 326.9KB PDF | Date added | 10 May 2007 |
| Topics | Data Visualization, High Performance Computing | ||
| Downloads | 175 | ||
This paper considers spectral clustering and transductive inference for data with multiple views. A typical example is the web, which can be described by either the hyperlinks between web pages or the words occurring in web pages. When each view is represented as a graph, one may convexly combine the weight matrices or the discrete Laplacians for each graph, and then proceed with existing clustering or classification techniques. Such a solution might sound natural, but its underlying principle is not clear. Unlike this kind of methodology, it develops multiview spectral clustering via generalizing the normalized cut from a single view to multiple views.
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