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Information Science and Technology

Special Lecture at UTokyo "Linear Algebra"

Lecture Note (pdf)

Information Science and Technology

Special Lecture at UTokyo "Linear Algebra"

Lecture Note (pdf)

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Lecturer

MathWorks Professor of Mathematics, Massachusetts Institute of Technology

※Affiliations and positions are as of the time of recording.

Special Lecture at UTokyo "Linear Algebra"

Content List

Lecture Note (pdf)

1-1 Importance of Linear Algebra

1-2 Two ways of understanding　a matrix times a vector

1-3 What is the "rank" ?

1-4 Applications of Linear Algebra

1-5 Five great problems of Linear Algebra or factorization of matrix

1-6 Factorization of symmetric matrix

1-7 Elimination to solve Ax=b

1-8 Gram-Schmidt method

1-9 Eigen values and Eigen vectors

1-10 Application of Eigen vector : Markov Process

1-11 Computing Linear Algebra

1-12 Linear Algebra #1 in MIT OCW

2-1 Importance of Linear Algebra

2-2 Rank of Matrix

2-3 Singular Values

2-4 Matrices of Data and Singular Values

Lecture Note (pdf)

1-1 Importance of Linear Algebra

1-2 Two ways of understanding　a matrix times a vector

1-3 What is the "rank" ?

1-4 Applications of Linear Algebra

1-5 Five great problems of Linear Algebra or factorization of matrix

1-6 Factorization of symmetric matrix

1-7 Elimination to solve Ax=b

1-8 Gram-Schmidt method

1-9 Eigen values and Eigen vectors

1-10 Application of Eigen vector : Markov Process

1-11 Computing Linear Algebra

1-12 Linear Algebra #1 in MIT OCW

2-1 Importance of Linear Algebra

2-2 Rank of Matrix

2-3 Singular Values

2-4 Matrices of Data and Singular Values

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HOME
Special Lecture at UTokyo "Linear Algebra"
Lecture Note (pdf)

Special Lecture at UTokyo "Linear Algebra"

Content List

Lecture Note (pdf)

1-1 Importance of Linear Algebra

1-2 Two ways of understanding　a matrix times a vector

1-3 What is the "rank" ?

1-4 Applications of Linear Algebra

1-5 Five great problems of Linear Algebra or factorization of matrix

1-6 Factorization of symmetric matrix

1-7 Elimination to solve Ax=b

1-8 Gram-Schmidt method

1-9 Eigen values and Eigen vectors

1-10 Application of Eigen vector : Markov Process

1-11 Computing Linear Algebra

1-12 Linear Algebra #1 in MIT OCW

2-1 Importance of Linear Algebra

2-2 Rank of Matrix

2-3 Singular Values

2-4 Matrices of Data and Singular Values

Lecture Note (pdf)

1-1 Importance of Linear Algebra

1-2 Two ways of understanding　a matrix times a vector

1-3 What is the "rank" ?

1-4 Applications of Linear Algebra

1-5 Five great problems of Linear Algebra or factorization of matrix

1-6 Factorization of symmetric matrix

1-7 Elimination to solve Ax=b

1-8 Gram-Schmidt method

1-9 Eigen values and Eigen vectors

1-10 Application of Eigen vector : Markov Process

1-11 Computing Linear Algebra

1-12 Linear Algebra #1 in MIT OCW

2-1 Importance of Linear Algebra

2-2 Rank of Matrix

2-3 Singular Values

2-4 Matrices of Data and Singular Values

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The 8th SCERU Public Seminar Linking Ukraine and the Indo-Pacific: Maintaining Global Unity

AY2023 SCERU Seminar / GraSPP Research Seminar

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The 8th SCERU Public Seminar Linking Ukraine and the Indo-Pacific: Maintaining Global Unity

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