Jensen's inequality is a powerful mathematical tool and one of the workhorses in statistical learning. Its applications therein include the EM algorithm, Bayesian estimation ...
We present a method whereby an embodied agent using visual perception can efficiently create a model of a local indoor environment from its experience of moving within it. Our me...
Grace Tsai, Changhai Xu, Jingen Liu, Benjamin Kuip...
This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop e...
Jie Cheng, Russell Greiner, Jonathan Kelly, David ...
Graphs provide an excellent framework for interrogating symmetric models of measurement random variables and discovering their implied conditional independence structure. However,...
Combining probability and first-order logic has been the subject of intensive research during the last ten years. The most well-known formalisms combining probability and some sub...