Several real-world applications need to effectively manage and reason about large amounts of data that are inherently uncertain. For instance, pervasive computing applications mus...
Daisy Zhe Wang, Eirinaios Michelakis, Minos N. Gar...
—We propose a unified graphical model that can represent both the causal and noncausal relationships among random variables and apply it to the image segmentation problem. Specif...
Many algorithms and applications involve repeatedly solving variations of the same inference problem; for example we may want to introduce new evidence to the model or perform upd...
Umut A. Acar, Alexander T. Ihler, Ramgopal R. Mett...
We present a novel and intuitive framework for building modular vision systems for complex tasks such as surveillance applications. Inspired by graphical models, especially factor...
We study the computational and sample complexity of parameter and structure learning in graphical models. Our main result shows that the class of factor graphs with bounded degree...