| S# |
Lecture |
Course |
Institute |
Instructor |
Discipline |
| 1476 |
Lecture 19 Conditional Probability
|
Mathematics for Computer Science (M-I-T) (Fall 2010)
|
MIT
|
Tom Leighton
|
Basic and Health Sciences
|
| 1477 |
|
Mathematics for Computer Science (M-I-T) (Fall 2010)
|
MIT
|
Tom Leighton
|
Basic and Health Sciences
|
| 1478 |
|
Mathematics for Computer Science (M-I-T) (Fall 2010)
|
MIT
|
Tom Leighton
|
Basic and Health Sciences
|
| 1479 |
Lecture 21 Random Variables
|
Mathematics for Computer Science (M-I-T) (Fall 2010)
|
MIT
|
Tom Leighton
|
Basic and Health Sciences
|
| 1480 |
|
Mathematics for Computer Science (M-I-T) (Fall 2010)
|
MIT
|
Tom Leighton
|
Basic and Health Sciences
|
| 1481 |
Lecture 23 Expectation II
|
Mathematics for Computer Science (M-I-T) (Fall 2010)
|
MIT
|
Tom Leighton
|
Basic and Health Sciences
|
| 1482 |
Lecture 24 Large Deviations
|
Mathematics for Computer Science (M-I-T) (Fall 2010)
|
MIT
|
Tom Leighton
|
Basic and Health Sciences
|
| 1483 |
|
Mathematics for Computer Science (M-I-T) (Fall 2010)
|
MIT
|
Tom Leighton
|
Basic and Health Sciences
|
| 1484 |
Lecture 3 Strong Induction
|
Mathematics for Computer Science (M-I-T) (Fall 2010)
|
MIT
|
Tom Leighton
|
Basic and Health Sciences
|
| 1485 |
Lecture 4 Number Theory I
|
Mathematics for Computer Science (M-I-T) (Fall 2010)
|
MIT
|
Marten van Dijk
|
Basic and Health Sciences
|
| 1486 |
Lecture 5 Number Theory II
|
Mathematics for Computer Science (M-I-T) (Fall 2010)
|
MIT
|
Marten van Dijk
|
Basic and Health Sciences
|
| 1487 |
Lecture 6 Graph Theory and Coloring
|
Mathematics for Computer Science (M-I-T) (Fall 2010)
|
MIT
|
Tom Leighton
|
Basic and Health Sciences
|
| 1488 |
Lecture 7 Matching Problems
|
Mathematics for Computer Science (M-I-T) (Fall 2010)
|
MIT
|
Tom Leighton
|
Basic and Health Sciences
|
| 1489 |
Lecture 8 Graph Theory II Minimum Spanning Trees
|
Mathematics for Computer Science (M-I-T) (Fall 2010)
|
MIT
|
Marten van Dijk
|
Basic and Health Sciences
|
| 1490 |
Lecture 9 Communication Networks
|
Mathematics for Computer Science (M-I-T) (Fall 2010)
|
MIT
|
Marten van Dijk
|
Basic and Health Sciences
|
| 1491 |
Lecture 10: Survey of Difficulties with Ax = b (M-I-T)
|
Matrix Methods in Data Analysis, Signal Processing, and Machine Learning (Spring 2018) (M-I-T)
|
MIT
|
Prof. Dr. Gilbert Strang
|
Basic and Health Sciences
|
| 1492 |
Lecture 11: Minimizing ‖x‖ Subject to Ax = b (M-I-T)
|
Matrix Methods in Data Analysis, Signal Processing, and Machine Learning (Spring 2018) (M-I-T)
|
MIT
|
53
|
Basic and Health Sciences
|
| 1493 |
Lecture 12: Computing Eigenvalues and Singular Values (M-I-T)
|
Matrix Methods in Data Analysis, Signal Processing, and Machine Learning (Spring 2018) (M-I-T)
|
MIT
|
Prof. Dr. Gilbert Strang
|
Basic and Health Sciences
|
| 1494 |
Lecture 13: Randomized Matrix Multiplication (M-I-T)
|
Matrix Methods in Data Analysis, Signal Processing, and Machine Learning (Spring 2018) (M-I-T)
|
MIT
|
Prof. Dr. Gilbert Strang
|
Basic and Health Sciences
|
| 1495 |
Lecture 14: Low Rank Changes in A and Its Inverse (M-I-T)
|
Matrix Methods in Data Analysis, Signal Processing, and Machine Learning (Spring 2018) (M-I-T)
|
MIT
|
Prof. Dr. Gilbert Strang
|
Basic and Health Sciences
|
| 1496 |
Lecture 15: Matrices A(t) Depending on t, Derivative = dA/dt (M-I-T)
|
Matrix Methods in Data Analysis, Signal Processing, and Machine Learning (Spring 2018) (M-I-T)
|
MIT
|
Prof. Dr. Gilbert Strang
|
Basic and Health Sciences
|
| 1497 |
Lecture 16: Derivatives of Inverse and Singular Values (M-I-T)
|
Matrix Methods in Data Analysis, Signal Processing, and Machine Learning (Spring 2018) (M-I-T)
|
MIT
|
Prof. Dr. Gilbert Strang
|
Basic and Health Sciences
|
| 1498 |
Lecture 17: Rapidly Decreasing Singular Values (M-I-T)
|
Matrix Methods in Data Analysis, Signal Processing, and Machine Learning (Spring 2018) (M-I-T)
|
MIT
|
Prof. Dr. Alex Townsend
|
Basic and Health Sciences
|
| 1499 |
Lecture 18: Counting Parameters in SVD, LU, QR, Saddle Points (M-I-T)
|
Matrix Methods in Data Analysis, Signal Processing, and Machine Learning (Spring 2018) (M-I-T)
|
MIT
|
Prof. Dr. Gilbert Strang
|
Basic and Health Sciences
|
| 1500 |
Lecture 19: Saddle Points Continued, Maxmin Principle (M-I-T)
|
Matrix Methods in Data Analysis, Signal Processing, and Machine Learning (Spring 2018) (M-I-T)
|
MIT
|
Prof. Dr. Gilbert Strang
|
Basic and Health Sciences
|
