This schedule should be considered tentative and subject to change, at least until it actually takes place!

Week Date Notes, Readings, and HW
1 Tue, Feb 09 Introduction
Thu, Feb 11 Optimization and linear algebra refresher
2 Tue, Feb 16 Regularized linear least squares
Thu, Feb 18 Sparse least squares and iterations
3 Tue, Feb 23 Stochastic gradients, scaling, and Newton
Thu, Feb 25 Randomized numerical linear algebra
4 Tue, Mar 02 Latent factor models
Thu, Mar 04 SVD and other low-rank decompositions
5 Tue, Mar 09 Wellness day
Thu, Mar 11 Non-negative matrix factorization
6 Tue, Mar 16 Tensor basics, HOSVD, Tucker, and ALS
Thu, Mar 18 CP decomposition and algorithms, CUR and tensor trains
7 Tue, Mar 23 Nonlinear dimensionality reduction
Thu, Mar 25 Function approximation fundamentals
8 Tue, Mar 30 Low-dim structure in function approximation
Thu, Apr 01 Low-dim structure in function approximation
9 Tue, Apr 06 Many interpretations of kernels
Thu, Apr 08 Approaches to kernel selection
10 Tue, Apr 13 Computing with kernels
Thu, Apr 15 Scalable kernel methods
11 Tue, Apr 20 Matrices associated with graphs
Thu, Apr 22 Function approximation on graphs
12 Tue, Apr 27 Graph clustering and partitioning
Thu, Apr 29 Centrality measures
13 Tue, May 04 Learning linear system dynamics
Thu, May 06 Learned dynamics and extrapolation
14 Tue, May 11 Koopman theory and lifting
Thu, May 13 Learning nonlinear dynamics