The Information Bottleneck EM Algorithm

Understand

Learning with hidden variables is a central challenge in probabilistic graphical models that has important implications for many real-life problems.

• The classical approach is using the Expectation Maximization (EM) algorithm.
• This algorithm, however, can get trapped in local maxima.
• In this paper we explore a new approach that is based on the Information Bottleneck principle.