Co-Clustering by Bipartite Spectral Graph Partitioning for Out-of-Tutor Prediction

@inproceedings{Trivedi2012CoClusteringBB,
  title={Co-Clustering by Bipartite Spectral Graph Partitioning for Out-of-Tutor Prediction},
  author={Shubhendu Trivedi and Zachary A. Pardos and G{\'a}bor N. S{\'a}rk{\"o}zy and Neil T. Heffernan},
  booktitle={EDM},
  year={2012}
}
Learning a more distributed representation of the input feature space is a powerful method to boost the performance of a given predictor. Often this is accomplished by partitioning the data into homogeneous groups by clustering so that separate models could be trained on each cluster. Intuitively each such predictor is a better representative of the members of the given cluster than a predictor trained on the entire data-set. Previous work has used this basic premise to construct a simple yet… CONTINUE READING

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