# Density Estimation by Total Variation Regularization

@inproceedings{Mizera2005DensityEB, title={Density Estimation by Total Variation Regularization}, author={Ivan Mizera}, year={2005} }

- Published 2005

L1 penalties have proven to be an attractive regularization device for nonparametric regression, image reconstruction, and model selection. For function estimation, L1 penalties, interpreted as roughness of the candidate function measured by their total variation, are known to be capable of capturing sharp changes in the target function while still maintaining a general smoothing objective. We explore the use of penalties based on total variation of the estimated density, its square root, and… CONTINUE READING

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