Corpus ID: 208175538

Bayesian sparse convex clustering via global-local shrinkage priors

@article{Shimamura2019BayesianSC,
  title={Bayesian sparse convex clustering via global-local shrinkage priors},
  author={Kaito Shimamura and Shuichi Kawano},
  journal={ArXiv},
  year={2019},
  volume={abs/1911.08703}
}
  • Kaito Shimamura, Shuichi Kawano
  • Published in ArXiv 2019
  • Computer Science, Mathematics
  • Sparse convex clustering is to cluster observations and conduct variable selection simultaneously in the framework of convex clustering. Although the weighted $L_1$ norm as the regularization term is usually employed in the sparse convex clustering, this increases the dependence on the data and reduces the estimation accuracy if the sample size is not sufficient. To tackle these problems, this paper proposes a Bayesian sparse convex clustering via the idea of Bayesian lasso and global-local… CONTINUE READING

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