# Calendar

## Links to Slides, Relevant Chapters in [WM22] and Extra Reading, and Presenters

- Lecture 1
- Introduction to Low-Dimensional Models
- John Wright

- Chapters 2-6, WM22

- Lecture 2
- Chapter 8, WM22

- Lecture 3
- Chapters 7, 9, WM22
- Survey: “From Symmetry to Geometry: Tractable Nonconvex Problems”

- Lecture 4
- Learning Low-Dimensional Structures via Deep Networks
- Sam Buchanan, Zhihui Zhu

- Chapter 16, WM22
- Deep Networks and the Multiple Manifold Problem
- Deep Networks Provably Classify Data on Curves
- A Geometric Analysis of Neural Collapse with Unconstrained Features
- On the Optimization Landscape of Neural Collapse under MSE Loss: Global Optimality with Unconstrained Features
- Robust Training under Label Noise by Over-parameterization

- Lecture 5