
L1General
 Referenced in 1 article
[sw32150]
 L1General  Matlab code for solving L1regularization problems.

l1kdeconv
 Referenced in 0 articles
[sw19671]
 R package l1kdeconv. Deconvolution for LINCS L1000 Data. LINCS L1000 is a highthrougphput technology that allows the gene expression measurement in a large number of ...

l1_logreg
 Referenced in 1 article
[sw25401]
 l1_logreg: A largescale solver for l1regularized logistic regression problems. l1_logreg is an implementation of the interiorpoint method for l1regularized logistic regression described in the paper, ...

l1_ls
 Referenced in 9 articles
[sw14267]
 l1_ls: Simple Matlab Solver for l1regularized Least Squares Problems. l1_ls is a Matlab implementation of the interiorpoint method for ell_1regularized least squares described in the ...

L1MAGIC
 Referenced in 30 articles
[sw12430]
 L1MAGIC is a collection of MATLAB routines for solving the convex optimization programs central to compressive sampling. The algorithms are based on standard interiorpoint methods, ...

L1pack
 Referenced in 1 article
[sw32621]
 R package L1pack: Routines for L1 Estimation. L1 estimation for linear regression, density, distribution function, quantile function and random number generation for univariate and multivariate ...

L1Packv2
 Referenced in 2 articles
[sw00497]
 L1Packv2: A Mathematica package for minimizing an L<sub>1</sub>penalized functional

L1PMA
 Referenced in 2 articles
[sw21492]
 L1PMA: a Fortran 77 package for best L 1 piecewise monotonic data smoothing. Fortran 77 software is presented for the calculation of a best L1 ...

L1pred
 Referenced in 1 article
[sw25075]
 L1pred: A SequenceBased Prediction Tool for Catalytic Residues in Enzymes with the L1logreg Classifier. To understand enzyme functions, identifying the catalytic residues is a usual ...

L1TestPack
 Referenced in 13 articles
[sw20470]
 L1TestPack: A software to generate test instances for l_1 minimization problems. L1TestPack consists of several Matlab mfiles to generate test instances for the socalled Basis ...

L2CXCV
 Referenced in 2 articles
[sw26952]
 L2CXCV: A Fortran 77 package for least squares convex/concave data smoothing. Fortran 77 software is given for least squares smoothing to data values contaminated by ...

L2CXFT
 Referenced in 9 articles
[sw00498]
 A Fortran subroutine applies the method of {\itI. C. Demetriou} and {\itM. J. D. Powell} [IMA J. Numer. Anal. 11, No. 3, 433448 (1991; Zbl ...

L2MCX
 Referenced in 1 article
[sw14996]
 L2MCX: a Fortran 77 package for least squares data smoothing by nonnegative divided differences.

L2P
 Referenced in 0 articles
[sw05615]
 L2P  Create PNG images of LaTeX math expressions. L2P creates PNG images of mathematical expressions formatted in LaTeX. While it can convert a whole ...

L2P
 Referenced in 2 articles
[sw36456]
 L2P: An Algorithm for Estimating Heavytailed Outcomes. Many realworld prediction tasks have outcome (a.k.a. target or re sponse) variables that have characteristic heavytail distributions. Examples ...

L2Roe
 Referenced in 8 articles
[sw18355]
 L2Roe: A low dissipation version of Roe’s approximate Riemann solver for low Mach numbers. A modification of the Roe scheme called L2Roe for low dissipation ...

L2WPMA
 Referenced in 8 articles
[sw04326]
 Fortran software is developed that calculates a best piecewise monotonic approximation to n univariate data contaminated by random errors. The underlying method minimizes the weighted ...

L3toHorospere
 Referenced in 1 article
[sw11225]
 Central projection of hyperbolic space onto a horosphere. A horosphere is a surface in hyperbolic space that is isometric to the Euclidean plane. In order ...

L5Kit
 Referenced in 2 articles
[sw36636]
 L5Kit dataset: One Thousand and One Hours: Selfdriving Motion Prediction Dataset. Motivated by the impact of largescale datasets on ML systems we present the largest ...

LA
 Referenced in 0 articles
[sw05828]
 The LA library provides a C++ vector and matrix class with an interface to BLAS and LAPACK linear algebra libraries and a few additional features. ...