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On Pattern Recovery of The Fused Lasso
Confidence interval jackknife empirical likelihood risk measure
2016/1/25
Quantifying risks is of importance in insurance. In this paper, we employ the jackknife empirical likelihood method to construct confidence intervals for some risk measures and related quantities stud...
On Pattern Recovery of The Fused Lasso
Fused Lasso Non-asymptotic Pattern recovery Preconditioning
2016/1/20
We study the property of the Fused Lasso Signal Approximator(FLSA) for estimating a blocky signal sequence with additive noise.We transform the FLSA to an ordinary Lasso problem. By studying the prope...
The lasso penalizes a least squares regression by the sum of the absolute values
(L1-norm) of the coefficients. The form of this penalty encourages sparse solutions (with many
coefficien...
Fused Multiple Graphical Lasso
Fused Multiple Graphical Lasso
2012/11/23
In this paper, we consider the problem of estimating multiple graphical models simultaneously using the fused lasso penalty, which encourages adjacent graphs to share similar structures. A motivating ...
The group fused Lasso for multiple change-point detection
Mines ParisTech CBIO, Fontainebleau, France Institut Curie, Paris, France INSERM U900, Paris, France
2011/7/7
We present the group fused Lasso for detection of multiple change-points shared by a set of co-occurring one-dimensional signals.