The Eckart-Young Theorem
For any mxn matrix (operator acting on Euclidean space) we prove that the best finite rank approximation of this matrix in the norm sense is given by the truncated singular value decomposition. This is the Eckart-Young Theorem. This theorem also asserts that the smallest possible operator norm distance between the operator and a finite rank operator of rank l is the (l+1)st singular value. #mikethemathematician, #mikedabkowski, #profdabkowski

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Distinct Eigenvalues Have Linearly Independent Eigenvectors

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7. Eckart-Young: The Closest Rank k Matrix to A

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2.1.1 Launch: Low rank approximation
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[Session 10] Performance Measurement and Analysis (English)

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Operator Theory Lesson 1 - Boundedness!

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Terry Tao's GPT chatlog re: Jacobian conjecture

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Eckart–Young–Mirsky Theorem and Proof

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William Dunham, A tribute to Euler

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2026 Fields Medal: Hong Wang

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Proof of Fermat Last Theorem FROM SCRATCH

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Singular Value Decomposition (the SVD)

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A Once-in-a-Century Proof: The Kakeya Conjecture

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1986: How to Spot the Upper Class | That's Life! | BBC Archive

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11: Clairaut's Theorem Intuition - Valuable Vector Calculus

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The PROBLEM with Capitalism - Smarter Every Day 316

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The Scariest Chart in Electrical Engineering

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