Abstract. Markov random fields are often used to model high dimensional distributions in a number of applied areas. A number of recent papers have studied the problem of reconstruc...
In this paper, we investigate limiting behavior of linear dynamic systems driven by random stochastic matrices. We introduce and study the new concepts of partial ergodicity and 1-...
Kernel conditional random fields (KCRFs) are introduced as a framework for discriminative modeling of graph-structured data. A representer theorem for conditional graphical models...
We present randomized algorithms for two sorting problems. In the local sorting problem, a graph is given in which each vertex is assigned an element of a total order, and the task...
The task of selecting and ordering information appears in multiple contexts in text generation and summarization. For instance, methods for title generation construct a headline b...