Frobenius vs Spectral Norm - Quant Trader Interview Question
Difficulty: Medium
Category: Linear Algebra & Machine Learning
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Topics: linear-algebra, matrix-norms, frobenius-norm, spectral-norm
Problem Description
Let $A$ be a real-valued $m imes n$ matrix. The Frobenius norm of $A$, denoted $||A||_F$, is defined as the square root of the sum of the squares of its elements. The spectral norm of $A$, denoted $||A||_2$, is defined as the largest singular value of $A$.
Which of the following statements is always true for any real-valued $m imes n$ matrix $A$?
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