Multidimensional Data Analysis

Tensor Basics

8/30	Course overview Read Chapter 1
9/1	Matrix SVD Read Review Chapters A and B

9/6	Indexing and linearization Read Chapter 2
9/8	Basic tensor operations Read Sections 3.1-3.5 Homework 1 due

Tucker Decomposition

9/13	Finish basic tensor operations Read Sections 3.6-3.7
9/15	Overview of Tucker Read Chapter 5 Homework 2 due

9/20	Jury duty (no class)
9/22	Tucker structure Read Chapter 6

9/27	Tucker optimization problem Read Section 7.1 Homework 3 due
9/29	HOOI, HOSVD, and STHOSVD Read Sections 7.2-7.5

10/4	Tucker algorithms (continued)
10/6	Approximation error Read Chapter 8 Homework 4 due

10/11	Reconstruction
10/13	Fall Break (no class)

CP Decomposition

10/18	Tensor workshop (no class)
10/20	Overview of CP Read Chapter 9

10/25	Kruskal structure Read Chapter 10
10/27	CP-ALS Read Chapter 11 Homework 5 due

11/1	MTTKRP Read Section 3.8
11/3	Gradient-based optimization Read Review Chapter B Homework 6 due

11/8	CP gradient Read Chapter 12
11/10	CP-OPT Project proposal due

11/15	Gauss-Newton method Read Section B.2.6
11/17	CP-DGN Read Chapter 13 Homework 7 due

11/22	Thanksgiving Break (no class)
11/24	Thanksgiving Break (no class)

Special Topics

11/29	Comparison of CP methods Project progress report due
12/1	Comparison of Tucker methods

12/6	Tensor Train structure
12/8	TT-Rounding Homework 8 due

12/13

Project presentations (9am)