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[theory-seminar] Theory Lunch 10/31 - Mona Azadkia

Neha Gupta nehgupta at
Wed Oct 30 09:25:46 PDT 2019

Hi everyone,

This Thursday at theory lunch, Mona will tell us about "A Simple Measure of Conditional Dependence" (abstract below). As usual, please join us from noon - 1pm in Gates 463A.


A Simple Measure of Conditional Dependence

We propose a coefficient of conditional dependence between two random variables Y and Z given a set of other variables X1, . . . , Xp, based on an i.i.d. sample. The coefficient has a long list of desirable properties, the most important of which is that under absolutely no distributional assumptions, it converges to a limit in [0, 1], where the limit is 0 if and only if Y and Z are conditionally independent given X1, . . . , Xp, and is 1 if and only if Y is equal to a measurable function of Z given X1, . . . , Xp. Using this statistic, we devise a new variable selection algorithm, called Feature Ordering by Conditional Independence (FOCI), which is model-free, has no tuning parameters, and is provably consistent under sparsity assumptions. A number of applications to synthetic and real datasets are worked out.

This is joint work with Sourav Chatterjee.



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