Probabilistic Decision Graphs (PDGs) are a class of graphical models that can naturally encode some context specific independencies that cannot always be efficiently captured by...
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-...
Real-time streaming signal processing systems typically desire high throughput and low latency. Many such systems can be modeled as synchronous data flow graphs. In this paper, w...
Jing Lin, Akshaya Srivatsa, Andreas Gerstlauer, Br...
Markov Random Fields (MRF's) can be used for a wide variety of vision problems. In this paper we focus on MRF's with two-valued clique potentials, which form a generaliz...
Quadratic program relaxations are proposed as an alternative to linear program relaxations and tree reweighted belief propagation for the metric labeling or MAP estimation problem...