Graph transduction via alternating minimization

@inproceedings{Wang2008GraphTV,
  title={Graph transduction via alternating minimization},
  author={Jun Wang and Tony Jebara and Shih-Fu Chang},
  booktitle={ICML},
  year={2008}
}
Graph transduction methods label input data by learning a classification function that is regularized to exhibit smoothness along a graph over labeled and unlabeled samples. In practice, these algorithms are sensitive to the initial set of labels provided by the user. For instance, classification accuracy drops if the training set contains weak labels, if imbalances exist across label classes or if the labeled portion of the data is not chosen at random. This paper introduces a propagation… CONTINUE READING
Highly Influential
This paper has highly influenced 13 other papers. REVIEW HIGHLY INFLUENTIAL CITATIONS
Highly Cited
This paper has 177 citations. REVIEW CITATIONS
88 Citations
4 References
Similar Papers

Citations

Publications citing this paper.
Showing 1-10 of 88 extracted citations

178 Citations

0102030'09'11'13'15'17
Citations per Year
Semantic Scholar estimates that this publication has 178 citations based on the available data.

See our FAQ for additional information.

Similar Papers

Loading similar papers…