Groups
Category
Expectation Maximization (EM) is an iterative algorithm to estimate parameters when some variables are hidden or unobserved.
The Information Bottleneck (IB) principle formalizes the tradeoff between compressing an input X and preserving information about a target Y using the objective min_{p(t|x)} I(X;T) - \beta I(T;Y).