Non-negative least squares

Known as: NNLS, Nonnegative least squares 
In mathematical optimization, the problem of non-negative least squares (NNLS) is a constrained version of the least squares problem where the… (More)
Wikipedia

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2016
2016
Sparse, non-negative signals occur in many applications. To recover such signals, estimation posed as non-negative least squares… (More)
  • figure 1
  • figure 2
  • figure 3
  • figure 4
Is this relevant?
2014
2014
Sparse coding is an active research subject in signal processing, computer vision, and pattern recognition. A novel method of… (More)
  • figure 1
  • figure 2
  • figure 3
  • table 1
  • table 2
Is this relevant?
2013
2013
A non-negative least squares classifier is proposed in this paper for classifying under-complete data. The idea is that unknown… (More)
  • table 1
  • table 2
  • table 3
  • table 4
  • figure 1
Is this relevant?
2013
2013
We present a new algorithm for nonnegative least-squares (NNLS). Our algorithm extends the unconstrained quadratic optimization… (More)
  • figure 1
  • figure 2
  • figure 3
  • figure 4
  • figure 5
Is this relevant?
2012
2012
In this work, the problem of constrained coil design is studied. Two approaches to this problem, namely the non-negative least… (More)
  • figure 1
  • table I
  • figure 2
  • figure 3
  • figure 4
Is this relevant?
2011
2011
Non-negative data are commonly encountered in numerous fields, making nonnegative least squares regression (NNLS) a frequently… (More)
Is this relevant?
2011
2011
We parallelize a version of the active-set iterative algorithm derived from the original works of Lawson and Hanson (1974) on… (More)
  • table 3.1
  • figure 5.1
  • table 7.1
  • table 7.2
  • table 7.3
Is this relevant?
2011
2011
mRNA-Seq technology has revolutionized the field of transcriptomics for identification and quantification of gene transcripts not… (More)
Is this relevant?
2005
2005
This paper contributes to the solution of the non-negative least squares problem (NNLS). The NNLS problem constitutes a… (More)
  • figure 2
  • figure 3
Is this relevant?
Highly Cited
1997
Highly Cited
1997
In this paper a modification of the standard algorithm for non-negativity-constrained linear least squares regression is proposed… (More)
  • table 1
  • table 2
Is this relevant?