Theoretical Statistics and Machine Learning

3 Hours

Examine concentration inequalities and asymptotic theory. Explore Hoeffding, Chernoff, Bernstein, Martingale-based methods, the Efron-Stein inequality, the Gaussian Lipschitz theorem, U statistics, uniform laws of large numbers, VC dimension, covering and packing. Practice high-dimensional covariance estimation and resampling. Statistics and Data Sciences 391P (Topic 6) and 384 (Topic 11) may not both be counted.