Lecture 14: Low Rank Changes in A and Its Inverse

Om kurset

Description In this lecture, Professor Strang introduces the concept of low rank matrices. He demonstrates how using the Sherman-Morrison-Woodbury formula is useful to efficiently compute how small changes in a matrix affect its inverse. Summary If \(A\) is changed by a rank-one matrix, so is its inverse. Woodbury-Morrison formula for those changes New data in least squares will produce these changes. Avoid recomputing over again with all data Note: Formula in class is correct in the textbook. Related section in textbook: III.1 Instructor: Prof. Gilbert Strang