Vincent Tan

Compressed Sensing with Structured Sparsity | Canonical Estimation in a Rare-Events Regime

Title: Canonical Estimation in a Rare-Events Regime by Vincent Tan Abstract: We propose a general methodology for performing statistical inference within a `rare-events regime’ that was recently suggested by Wagner, Viswanath and Kulkarni. Our approach allows one to easily establish consistent estimators for a very large class of canonical estimation …

Large Deviations and Extensions for Learning Tree Models

Learning the structure of graphical models from data is a fundamental task in many scientific domains. I will describe analysis and applications of learning graphical models. We analyze the theoretical properties of a well-known structure learning algorithm known as the Chow-Liu algorithm (1968). The Chow-Liu algorithm learns the maximum-likelihood (ML) …