Learning with ℓ1 -graph for high dimensional data analysis

Jianchao Yang, Bin Cheng, Shuicheng Yan, Yun Fu, Thomas Huang

Research output: Chapter in Book/Report/Conference proceedingChapter


An informative graph, directed or undirected, is critical for those graph-orientated algorithms designed for data analysis, such as clustering, subspace learning, and semi-supervised learning. Data clustering often starts with a pairwise similarity graph and then translates into a graph partition problem [19], and thus the quality of the graph essentially determines the clustering quality.

Original languageEnglish (US)
Title of host publicationGraph Embedding for Pattern Analysis
Number of pages18
ISBN (Electronic)9781461444572
ISBN (Print)9781461444565
StatePublished - Jan 1 2013

ASJC Scopus subject areas

  • General Engineering


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