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Catching Change-points with Lasso
Zaid Harchaoui · Céline Lévy-Leduc

Mon Dec 03 10:30 AM -- 10:40 AM (PST) @

We propose a new approach for dealing with the estimation of the location of change-points in one-dimensional piecewise constant signals observed in white noise. Our approach consists in reframing this task in a variable selection context. We use a penalized least-squares criterion with a l1-type penalty for this purpose. We prove that, in an appropriate asymptotic framework, this method provides consistent estimators of the change-points. Then, we explain how to implement this method in practice by combining the LAR algorithm and a reduced version of the dynamic programming algorithm and we apply it to synthetic and real data.

Author Information

Zaid Harchaoui (University of Washington)
Céline Lévy-Leduc (GET/Telecom Paris)

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