We consider the computational complexity of probabilistic inference in Latent Dirichlet Allocation (LDA). First, we study the problem of finding the maximum a posteriori (MAP)... Watch Video

The problem of learning to predict structured labels is of key importance in many applications. However, for general graph structure both learning and inference in this setting are... Watch Video

Linear Programming (LP) relaxations have become powerful tools for finding the most probable (MAP) configuration in graphical models. These relaxations can be solved efficiently... Watch Video