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We present the group fused Lasso for detection of multiple change-points shared by a set of co-occurring one-dimensional signals.
Matrices tridiagonales symétriques et matrices factorisables
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L. J. Vostrikova · 1981
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Estimating the number of change-points via schwarz criterion
Y. C. Yao · 1988
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Nonlinear total variation based noise removal algorithms
L. I. Rudin, S. Osher, and E. Fatemi · 1992
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Detection of abrupt changes: theory and application
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Nonparametric Methods in Change-Point Problems
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Penalized regressions: the bridge versus the lasso
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Adaptive detection of multiple change-points in asset price volatility
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Sparsity and smoothness via the fused lasso
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Using penalized contrasts for the change-point problem
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Bladder cancer stage and outcome by array-based comparative genomic hybridization
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A novel approach to detection of intrusions in computer networks via adaptive sequential and batch-sequential change-point detection methods
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Modeling recurrent DNA copy number alterations in array CGH data
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Catching change-points with lasso
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A regularized kernel-based approach to unsupervised audio segmentation
Z. Harchaoui, F. Vallet, A. Lung-Yut-Fong, and O. Cappe · 2009
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Detection and localization of change-points in high-dimensional network traffic data
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Properties and refinements of the fused lasso
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High resolution analysis of non-small cell lung cancer cell lines by whole genome tiling path array CGH
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Regional copy number-independent deregulation of transcription in cancer
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Detecting simultaneous change-points in multiple sequences
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Fast detection of multiple change-points shared by many signals using group LARS
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Online learning for matrix factorization and sparse coding
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