Andrea Montanari: Denoising, compressed sensing and low-rank
Statistical estimation and linear models: Basic definitions.
Examples and applications: Statistical learning, image denoising, etc. Linear
Limitations of linear smoothing. Nonlinear denoising. Wavelet thresholding and
some of its optimality
Compressed sensing. Average case theory and phase transitions.
Deterministic gurantees and oracle inequalities.
Approximate message passing algorithms and connections with statistical
Other convex optimization algorithms.
Low-rank matrix recovery. Matrix completion and hidden clique estimation.
Assessing uncertainty in high-dimensional statistical estimation. Theory and