There is a significant amount of redundancy between video frames or images that can be explained by considering these observations as samples of a light field function. By using a...
This paper presents novel likelihood estimation to be used for particle filter based object tracking. The likelihood estimation is built upon cascade object detector trained with ...
When a large amount of data are missing, or when multiple hidden nodes exist, learning parameters in Bayesian networks (BNs) becomes extremely difficult. This paper presents a lea...
This paper presents an approach to build Sparse Large Margin Classifiers (SLMC) by adding one more constraint to the standard Support Vector Machine (SVM) training problem. The ad...
We present a new approach to the old problem of adding side effects to purely functional languages. Our idea is to extend the language with "witnesses," which is based o...