01:03:19
BEE 3600 Office Hours 2020-04-15
Zoom Recording ID: 596257102 UUID: 4XPTGtKYT02pvWT0J/hR0Q== Meeting Time: 2020-04-15T21:57:06Z
14:38
2016 REU Cameron Ruhl CNF & PARADIM REU…
2016 REU Cameron Ruhl CNF & PARADIM REU Convocation
50:37
03 - Introduction to rank and matrix algebra…
03 - Introduction to rank and matrix algebra Session 3
2009-01-23 09:05:49+00
49:39
04 - Example problems and review of known…
04 - Example problems and review of known material Session 4
2009-01-26 09:06:45+00
50:13
19 - Matrices of Linear Transformations with…
19 - Matrices of Linear Transformations with Abstract Vectors Session 19
2009-03-02 13:19:12+00
48:47
29 - Determinants (Part 1) Session 29
2009-04-01 09:08:08+00
50:21
31 - Determinants Part 3 Session 31
2009-04-06 09:08:42+00
51:31
30 - Determinants Part 2 Session 30
2009-04-03 09:07:28+00
51:55
08 - Inverse matrices: Basic facts and its…
08 - Inverse matrices: Basic facts and its relationship with linear transformations Session 8
2009-02-04 09:05:35+00
49:24
34 - Eigenthings continued Session 34
2009-04-13 09:06:26+00
51:20
33 - Finding eigenvectors and eigenvalues Session…
33 - Finding eigenvectors and eigenvalues Session 33
2009-04-10 09:07:38+00
52:12
35 - Eigenthings continued and diagonalization…
35 - Eigenthings continued and diagonalization Session 35
2009-04-15 09:05:32+00
52:39
36 - Examples of eigen-thing problems and linear…
36 - Examples of eigen-thing problems and linear transformations Session 36
2009-04-17 09:06:55+00
50:32
41 - SVD decomposition cont'd Session 41
2009-04-29 09:06:42+00
45:58
18 - Abstract vectors continued and change of…
18 - Abstract vectors continued and change of basis Session 18
2009-02-27 09:11:20+00
01:05:38
ORIE 9000 Colloquium - Madeleine Udell:…
ORIE 9000 Colloquium - Madeleine Udell: Generalized Low Rank Models
Principal components analysis (PCA) is a well-known technique for approximating a data set represented by a matrix by a low rank matrix. Here, we extend the idea of PCA to handle arbitrary data sets…
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