Stochastics and Statistics Seminar Jing Lei, Carnegie Mellon University
Winners with Confidence: Discrete Argmin Inference with an Application to Model Selection
Abstract: We study the problem of finding the index of the minimum value of a vector from noisy observations. This problem is relevant in population/policy comparison, discrete maximum likelihood, and model selection. By integrating concepts and tools from cross-validation and differential privacy, we develop a test statistic that is asymptotically normal even in high-dimensional settings,…
