Probabilistic inference in graphical models is a prevalent task in statistics and artificial intelligence. The ability to perform this inference task efficiently is critical in l...
Coarse-to-fine approaches use sequences of increasingly fine approximations to control the complexity of inference and learning. These techniques are often used in NLP and visio...
We build on recent work on argumentation frameworks for generating desires and plans. We provide a rich instantiDung's abstract argumentation framework for (i) generating con...
We build on recent work on argumentation frameworks for generating desires and plans. We provide a rich instantiDung's abstract argumentation framework for (i) generating con...
Abstract. This tutorial explores the design space of heterogeneous synchronization, which is concerned with establishing consistency among artifacts that conform to different sche...