Least squares estimation with quadratic constraints (M*M = 0)

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SUMMARY

The discussion focuses on solving a least squares problem defined as min_{M} ||Y - M*X||^2, where M is a 3x3 rank 1 matrix constrained by M*M = 0_{3x3} and a zero trace. The participant highlights the simplicity of enforcing the zero trace constraint but expresses uncertainty regarding the quadratic constraint M*M = 0_{3x3}. It is noted that if M is nilpotent of degree 2 and rank 1, it can be represented in a specific basis as M=E_{13}, indicating a non-zero entry at position (1,3) and zeros elsewhere.

PREREQUISITES
  • Understanding of least squares optimization techniques
  • Familiarity with matrix algebra and properties of rank and nilpotent matrices
  • Knowledge of quadratic constraints in optimization problems
  • Experience with linear algebra concepts, particularly trace and matrix representation
NEXT STEPS
  • Research methods for enforcing quadratic constraints in optimization, specifically in least squares problems
  • Explore the properties and applications of nilpotent matrices in linear algebra
  • Study the formulation and solution of optimization problems with matrix variables
  • Learn about specialized optimization tools or libraries that handle quadratic constraints, such as CVXOPT or MATLAB's Optimization Toolbox
USEFUL FOR

Mathematicians, data scientists, and optimization engineers who are working on advanced least squares problems involving matrix constraints and require a deeper understanding of quadratic constraints and nilpotent matrices.

Michael02
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Hello there,

currently I am trying to solve a least squares problem of the following form:

[itex]min_{M}[/itex] ||Y - M*X||[itex]^2[/itex]

where M is a 3x3 matrix and Y and X are 3xN matrices. However, the matrix M is of a special form. It is a rank 1 matrix which satisfies M*M = 0[itex]_{3x3}[/itex] and the trace of M is zero, too.

Enforcing that the trace is zero seems rather easy, since it is a linear constraint. But I have no idea how to enforce M*M = 0[itex]_{3x3}[/itex], as it includes multiple quadratic constraints.

Does anyone have an idea how to solve this problem?
 
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If ##M## is nilpotent of degree ##2## and of rank ##1##, then there should be a basis, in which ##M## takes the form ##M=E_{13}##, i.e. a ##1## at position ##(1,3)## and ##0## elsewhere.
 

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