1.0Microsoft Researchhttps://www.microsoft.com/en-us/researchJeff Runninghttps://www.microsoft.com/en-us/research/people/jeffrunn/Ranking on Data Manifolds - Microsoft Researchrich600338<blockquote class="wp-embedded-content" data-secret="7AdKUCTDtn"><a href="https://www.microsoft.com/en-us/research/publication/ranking-data-manifolds/">Ranking on Data Manifolds</a></blockquote><iframe sandbox="allow-scripts" security="restricted" src="https://www.microsoft.com/en-us/research/publication/ranking-data-manifolds/embed/#?secret=7AdKUCTDtn" width="600" height="338" title="“Ranking on Data Manifolds” — Microsoft Research" data-secret="7AdKUCTDtn" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"></iframe><script>
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The Google search engine has enjoyed huge success with its web page ranking algorithm, which exploits global, rather than local, hyperlink structure of the web using random walks. Here we propose a simple universal ranking algorithm for data lying in the Euclidean space, such as text or image data. The core idea of our method […]