Generalization bounds depending on the margin of a classifier are a relatively recent development. They provide an explanation of the performance of state-of-the-art learning syste...
This paper addresses the problem of fully automated
mining of public space video data. A novel Markov Clustering
Topic Model (MCTM) is introduced which builds on
existing Dynami...
We develop an abstract model of information acquisition from redundant data. We assume a random sampling process from data which contain information with bias and are interested in...
We present a new method for segmenting actions into primitives and classifying them into a hierarchy of action classes. Our scheme learns action classes in an unsupervised manner ...
Traditional methods for creating classifiers have two main disadvantages. Firstly, it is time consuming to acquire, or manually annotate, the training collection. Secondly, the da...