Matrix Calculus for Linear Algebra - MIT 18.06 Spring 2020

Matrix Calculus for Linear Algebra - MIT 18.06 Spring 2020

The Julia Programming Language via YouTube Direct link

Gradients of Functions from Matrices to Scalars

13 of 20

13 of 20

Gradients of Functions from Matrices to Scalars

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Classroom Contents

Matrix Calculus for Linear Algebra - MIT 18.06 Spring 2020

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  1. 1 Matrix Calculus
  2. 2 Scalar Calculus
  3. 3 Emphasis on Linearization
  4. 4 Gradients
  5. 5 Geometrically
  6. 6 Matrix/Vector Product Rule
  7. 7 Gradients the straightforward but klunky way
  8. 8 Gradients the sophisticated way
  9. 9 Example f(x) = (Ax-b)'(Ax-b)
  10. 10 Gradient Notation
  11. 11 The Trace
  12. 12 Linear Functions of Matrices
  13. 13 Gradients of Functions from Matrices to Scalars
  14. 14 Vector to Vector Jacobians
  15. 15 How are Gradients Used
  16. 16 The Jacobian Matrix, vectors to vectors
  17. 17 A Key Point -- you don't have to write out the matrix elements
  18. 18 relationship to volumes
  19. 19 Matrices to Matrices
  20. 20 Derivatives of Matrix to Matrix Functions

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