Electronic Journal of Statistics
- Electron. J. Statist.
- Volume 11, Number 2 (2017), 4851-4870.
A sharp oracle inequality for Graph-Slope
Following recent success on the analysis of the Slope estimator, we provide a sharp oracle inequality in term of prediction error for Graph-Slope, a generalization of Slope to signals observed over a graph. In addition to improving upon best results obtained so far for the Total Variation denoiser (also referred to as Graph-Lasso or Generalized Lasso), we propose an efficient algorithm to compute Graph-Slope. The proposed algorithm is obtained by applying the forward-backward method to the dual formulation of the Graph-Slope optimization problem. We also provide experiments showing the practical applicability of the method.
Electron. J. Statist., Volume 11, Number 2 (2017), 4851-4870.
Received: June 2017
First available in Project Euclid: 30 November 2017
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Bellec, Pierre C.; Salmon, Joseph; Vaiter, Samuel. A sharp oracle inequality for Graph-Slope. Electron. J. Statist. 11 (2017), no. 2, 4851--4870. doi:10.1214/17-EJS1364. https://projecteuclid.org/euclid.ejs/1512032447