A Sequence of Relaxations Constraining Hidden Variable Models

Understand

Many widely studied graphical models with latent variables lead to nontrivial constraints on the distribution of the observed variables.

• Inspired by the Bell inequalities in quantum mechanics, we refer to any linear inequality whose violation rules out some latent variable model as a "hidden variable test" for that model.
• Our main contribution is to introduce a sequence of relaxations which provides progressively tighter hidden variable tests.
• We demonstrate applicability to mixtures of sequences of i.i.d.