This paper develops a probabilistic framework that can model and predict group activity over time on online social media. Users of social media sites such as Flickr often face the...
We describe a new tagging model where the states of a hidden Markov model (HMM) estimated by unsupervised learning are incorporated as the features in a maximum entropy model. Our...
This paper presents a Japanese information retrieval method using the dependency relationship between words and semantic and statistical information about them. Our method gives a...
In this paper, we consider the problem of robust localization of faces and some of their facial features. The task arises e.g. in the medical field of visual analysis of facial p...
Matthias Zobel, Arnd Gebhard, Dietrich Paulus, Joa...
We present a new dynamic probabilistic state exploration algorithm based on hash compaction. Our method has a low state omission probability and low memory usage that is independen...
William J. Knottenbelt, Mark Mestern, Peter G. Har...