Lasso

Known as: LassoSoft, Lasso programming language, .lasso 
Lasso is an application server and server management interface used to develop internet applications and is a general-purpose, high-level programming… (More)
Wikipedia

Topic mentions per year

Topic mentions per year

1993-2018
020040019932018

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2011
Highly Cited
2011
This is equivalent to minimizing the sum of squares with a constraint of the form Σ |βj| s. It is similar to ridge regression… (More)
  • table 1
  • figure 1
  • figure 2
Is this relevant?
Highly Cited
2010
Highly Cited
2010
We consider the group lasso penalty for the linear model. We note that the standard algorithm for solving the problem assumes… (More)
  • figure 1
  • figure 2
  • figure 3
Is this relevant?
Highly Cited
2009
Highly Cited
2009
We propose a new penalty function which, when used as regularization for empirical risk minimization procedures, leads to sparse… (More)
  • figure 1
  • figure 2
  • figure 3
  • figure 4
  • table 1
Is this relevant?
Highly Cited
2007
Highly Cited
2007
The group lasso is an extension of the lasso to do variable selection on (predefined) groups of variables in linear regression… (More)
  • figure 1
  • table 1
  • table 2
  • figure 2
  • table 3
Is this relevant?
Highly Cited
2007
Highly Cited
2007
We exhibit an approximate equivalence between the Lasso es-timator and Dantzig selector. For both methods we derive parallel… (More)
Is this relevant?
Highly Cited
2006
Highly Cited
2006
Sparsity or parsimony of statistical models is crucial for their proper interpretations, as in sciences and social sciences… (More)
  • figure 1
  • figure 2
  • table 1
Is this relevant?
Highly Cited
2006
Highly Cited
2006
The lasso is a popular technique for simultaneous estimation and variable selection. Lasso variable selection has been shown to… (More)
  • figure 1
  • table 1
  • table 2
  • table 3
  • table 4
Is this relevant?
Highly Cited
2005
Highly Cited
2005
The Lasso estimate for linear regression parameters can be interpreted as a Bayesian posterior mode estimate when the regression… (More)
  • figure 1
  • table 1
  • figure 2
  • figure 3
  • figure 4
Is this relevant?
Highly Cited
2004
Highly Cited
2004
The lasso penalizes a least squares regression by the sum of the absolute values (L1-norm) of the coefficients. The form of this… (More)
  • figure 1
  • figure 2
  • figure 3
  • figure 4
  • figure 5
Is this relevant?
Highly Cited
1999
Highly Cited
1999
Proposed by Tibshirani (1996), the LASSO (least absolute shrinkage and selection operator) estimates a vector of regression… (More)
  • table 6.1
Is this relevant?