Course III: Cynthia Rush - High-dimensional Statistics and Approximate Message Passing Algorithms

High-dimensional Statistics and Approximate Message Passing Algorithms
Lecturer: Cynthia Rush (Columbia)

Explore high-dimensional statistics and approximate message passing algorithms in this comprehensive lecture from the Extended Program on Randomness and Learning on Networks. Delve into advanced statistical concepts presented by Cynthia Rush from Columbia University as part of a month-long program at the Instituto de Matemática Pura e Aplicada (IMPA). Gain insights into cutting-edge research in discrete probability, statistics, and related fields through this 1-hour 22-minute session. Participate in a rich learning environment featuring talks by researchers, minicourses in statistics for PhD students, collaborative work, and open problem sessions. Discover opportunities for financial aid and potential funding for participants from RandNET institutions in Europe and Chile.

Lecture 1: High Dimensional Statistics
Lecture 2: High Dimensional Statistics
Lecture 3: Empirical Risk Estimation
Lecture 4: Approximate Message Passing algorithms
Lecture 5: Low Rank Matrix Estimation
Lecture 6: Generalized Linear Models