Mimic and Classify : A meta-algorithm for Conditional Independence Testing

1 code implementation • 25 Jun 2018 • Rajat Sen, Karthikeyan Shanmugam, Himanshu Asnani, Arman Rahimzamani, Sreeram Kannan

Given independent samples generated from the joint distribution $p(\mathbf{x},\mathbf{y},\mathbf{z})$, we study the problem of Conditional Independence (CI-Testing), i. e., whether the joint equals the CI distribution $p^{CI}(\mathbf{x},\mathbf{y},\mathbf{z})= p(\mathbf{z}) p(\mathbf{y}|\mathbf{z})p(\mathbf{x}|\mathbf{z})$ or not.

Potential Conditional Mutual Information: Estimators, Properties and Applications

no code implementations • 13 Oct 2017 • Arman Rahimzamani, Sreeram Kannan

We define the potential conditional mutual information as the conditional mutual information calculated with a modified joint distribution p_{Y|X, Z} q_{X, Z}, where q_{X, Z} is a potential distribution, fixed airport.

Time Series Time Series Analysis