We describe computationally efficient methods for learning mixtures in which each component is a directed acyclic graphical model (mixtures of DAGs or MDAGs). We argue that simple...
Bo Thiesson, Christopher Meek, David Maxwell Chick...
High dimensional structured data such as text and images is often poorly understood and misrepresented in statistical modeling. The standard histogram representation suffers from ...
We describe a novel approach to unsupervised learning of the events that make up a script, along with constraints on their temporal ordering. We collect naturallanguage descriptio...
Michaela Regneri, Alexander Koller, Manfred Pinkal
We present a machine learning approach for the task of ranking previously answered questions in a question repository with respect to their relevance to a new, unanswered referenc...
Previous works have demonstrated that the face recognition performance can be improved significantly in low dimensional linear subspaces. Conventionally, principal component analy...