Multidimensional Data Analysis

Introduction and Review

8/24 Tensor terminology and matrix SVD
8/26 Example applications

8/31 Computational models and efficiency
9/2 Linear algebra and optimization

Tensor Operations

9/7 Indexing and vectorization
9/9 Tensor unfolding

9/14 Basic tensor-vector operations
9/16 Basic tensor-matrix operations

Tucker Decomposition

9/21 Tucker structure
9/23 Applying Tucker

9/28 Tucker optimization problem
9/30 HOSVD, ST-HOSVD, and HOOI

10/5 Error analysis
10/7 Fall Break (no class)

10/12 Error analysis (continued)
10/14 Complexity analysis

10/19 Algorithm implementations
10/21 Algorithmic comparisons

CP Decomposition

10/26 Kruskal structure
10/28 Tensor rank

11/2 CP uniqueness
11/4 ALS derivation

11/9 ALS computation and complexity
11/11 CP approximation of EEM data

11/16 Optimization methods background
11/18 CP-OPT (Quasi-Newton methods)

11/23 CP-DGN (Damped Gauss-Newton method)
Project data proposals due
11/25 Thanksgiving Break (no class)

11/30 CP-DGN (continued)
12/2 CP with missing data

12/10 Project presentations (2pm)