ACCAMS: Additive Co-Clustering to Approximate Matrices Succinctly

@article{Beutel2015ACCAMSAC,
  title={ACCAMS: Additive Co-Clustering to Approximate Matrices Succinctly},
  author={Alex Beutel and Amr Ahmed and Alex Smola},
  journal={Proceedings of the 24th International Conference on World Wide Web},
  year={2015}
}
Matrix completion and approximation are popular tools to capture a user's preferences for recommendation and to approximate missing data. Instead of using low-rank factorization we take a drastically different approach, based on the simple insight that an additive model of co-clusterings allows one to approximate matrices efficiently. This allows us to build a concise model that, per bit of model learned, significantly beats all factorization approaches in matrix completion. Even more… Expand
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