Skip to search formSkip to main contentSkip to account menu

Least squares

Known as: Least squares method, Least-squares fit, LS 
The method of least squares is a standard approach in regression analysis to the approximate solution of overdetermined systems, i.e., sets of… 
Wikipedia (opens in a new tab)

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2008
Highly Cited
2008
Least-squares variance component estimation (LS-VCE) is a simple, flexible and attractive method for the estimation of unknown… 
Highly Cited
2005
Highly Cited
2005
Fitting standard shapes or curves to incomplete data (which represent only a small part of the curve) is a notoriously difficult… 
Highly Cited
2004
Highly Cited
2004
Localization of mobile phones is of considerable interest in wireless communications. In this correspondence, two algorithms are… 
Highly Cited
2000
Highly Cited
2000
The method of support vector machines (SVM's) has been developed for solving classification and static function approximation… 
Highly Cited
1999
Highly Cited
1999
Abstract. A probabilistic justification is given for using the integer least-squares (LS) estimator. The class of admissible… 
Highly Cited
1994
Highly Cited
1994
A solution of the least-squares two-dimensional phase-unwrapping problem is presented that is simpler to understand and implement… 
Highly Cited
1991
Highly Cited
1991
Constrained-least-squares (CLS) and weighted-least-squares (WLS) mixing models for generating fraction images derived from remote… 
Highly Cited
1985
Highly Cited
1985
The Adaptive Least Squares Correlation is a very potent and flexible technique for all kinds of data matching problems. Here its… 
Highly Cited
1982
Highly Cited
1982
We attempt to give a general definition of the nonlinear least squares inverse problem. First, we examine the discrete problem… 
Review
1976
Review
1976
The technique of least-squares-fit-to-a-polynominal smoothing of uniformly spaced digital data by convoluting the data with a…