Abstract. We propose a generative approach to the problem of labeling images containing configurations of objects from multiple classes. The main building blocks are dense statisti...
This paper discusses building complex classifiers from a single labeled example and vast number of unlabeled observation sets, each derived from observation of a single process or...
Supervised sequence-labeling systems in natural language processing often suffer from data sparsity because they use word types as features in their prediction tasks. Consequently...
We consider the problem of parsing facial features from an image labeling perspective. We learn a per-pixel unary classifier, and a prior over expected label configurations, allow...
Supervised text categorization is a machine learning task where a predefined category label is automatically assigned to a previously unlabelled document based upon characteristic...