| Publisher | University of Waterloo | ||
|---|---|---|---|
| Format | 264.3KB PDF | Date added | 19 Nov 2006 |
| Topics | Embedded Systems, Data Visualization, High Performance Computing | ||
| Downloads | 61 | ||
The authors usually endow the investigated objects with pairwise relationships, which can be illustrated as graphs. Naively squeezing the complex relationships into pairwise ones will inevitably lead to loss of information which can be expected valuable for the learning tasks however. Therefore it considers using hypergraphs in-stead to completely represent complex relationships among the objects of the interest, and thus the problem of learning with hypergraphs arises. The main contribution in this paper is to generalize the powerful methodology of spectral clustering which originally operates on undirected graphs to hypergraphs, and further develop algorithms for hypergraph embedding and transductive classification on the basis of the spectral hypergraph clustering approach.
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