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Frobenius inner product

Creator
Creator
Seonglae ChoSeonglae Cho
Created
Created
2025 Mar 4 1:12
Editor
Editor
Seonglae ChoSeonglae Cho
Edited
Edited
2025 Jun 2 16:43
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Generalized inner product for matrix

With an inner product structure, we can calculate 'similarity' measures like distances and angles, and define geometric
Orthogonality
. It is used to measure "distances between matrices" and to calculate gradients in optimization problems using inner products.
Using
Matrix Trace

Frobenius norm

 
 
 
Frobenius inner product
In mathematics, the Frobenius inner product is a binary operation that takes two matrices and returns a scalar. It is often denoted ⟨ A , B ⟩ F {\displaystyle \langle \mathbf {A} ,\mathbf {B} \rangle _{\mathrm {F} }} . The operation is a component-wise inner product of two matrices as though they are vectors, and satisfies the axioms for an inner product. The two matrices must have the same dimension—same number of rows and columns—but are not restricted to be square matrices.
Frobenius inner product
https://en.wikipedia.org/wiki/Frobenius_inner_product
 
 

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Frobenius inner product
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