Fast and Flexible ADMM Algorithms for Trend Filtering

  title={Fast and Flexible ADMM Algorithms for Trend Filtering},
  author={Aaditya Ramdas and Ryan J. Tibshirani},
This paper presents a fast and robust algorithm for trend filtering, a recently developed nonparametric regression tool. It has been shown that, for estimating functions whose derivatives are of bounded variation, trend filtering achieves the minimax optimal error rate, while other popular methods like smoothing splines and kernels do not. Standing in the way of a more widespread practical adoption, however, is a lack of scalable and numerically stable algorithms for fitting trend filtering… CONTINUE READING
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A Practical Guide to Splines

  • C. de Boor
  • 1978
Highly Influential
3 Excerpts

A dynamic programming algorithm for the fused lasso and L 0segmentation ’

  • N. Johnson
  • Journal of Computational and Graphical Statistics
  • 2013
Highly Influential
3 Excerpts

Coordinate descent, on the other hand, is quite far off (although we note that it does deliver a visually perfect piecewise linear fit after nearly 100,000 iterations)

  • Kim
  • 2009
Highly Influential
2 Excerpts

Rn×n is kth order falling factorial basis matrix, defined over

  • H H
  • 2014

argue that the appropriate extension of f̂ to the continuous domain is given by f̂(x

  • β̂n. Tibshirani, Wang
  • 2014

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