Nonparametric regression and classification with joint sparsity constraints

@inproceedings{Liu2008NonparametricRA,
  title={Nonparametric regression and classification with joint sparsity constraints},
  author={Han Liu and John D. Lafferty and Larry A. Wasserman},
  booktitle={NIPS},
  year={2008}
}
We propose new families of models and algorithms for high-dimensional nonparametric learning with joint sparsity constraints. Our approach is based on a regularization method that enforces common sparsity patterns across different function components in a nonparametric additive model. The algorithms employ a coordinate descent approach that is based on a functional soft-thresholding operator. The framework yields several new models, including multi-task sparse additive models, multi-response… CONTINUE READING
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