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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...
A fused lasso latent feature model for analyzing multi-sample aCGH data
Cancer DNA copy number False discovery rate Mutation
2015/8/21
Array-based comparative genomic hybridization (aCGH) enables the measurement of DNA copy number across thousands of locations in a genome. The main goals of analyzing aCGH data are to identify the reg...
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...
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.