To perform automatic, unconscious inference, the human brain must solve the "binding problem" by correctly grouping properties with objects. Temporal binding models like...
Bayesian methods for visual tracking model the likelihood of image measurements conditioned on a tracking hypothesis. Image measurements may, for example, correspond to various fi...
We consider the problem of estimating occurrence rates of rare events for extremely sparse data, using pre-existing hierarchies to perform inference at multiple resolutions. In pa...
Deepak Agarwal, Andrei Z. Broder, Deepayan Chakrab...
Abstract. We describe a probabilistic model, implemented as a dynamic Bayesian network, that can be used to predict nucleosome positioning along a chromosome based on one or more g...
Sheila M. Reynolds, Zhiping Weng, Jeff A. Bilmes, ...
As environments become smart in accordance with advances in ubiquitous computing technology, researchers are struggling to satisfy users' diverse and sophisticated demands. Th...
Jin Choi, Yong-il Cho, Kyusung Cho, Su-jung Bae, H...