For purpose of object recognition, we learn one discriminative classifier based on one prototype, using shape context distances as the feature vector. From multiple prototypes, th...
We consider the problem of improving named entity recognition (NER) systems by using external dictionaries--more specifically, the problem of extending state-of-the-art NER system...
In traditional text classification, a classifier is built using labeled training documents of every class. This paper studies a different problem. Given a set P of documents of a ...
NLP tasks are often domain specific, yet systems can learn behaviors across multiple domains. We develop a new multi-domain online learning framework based on parameter combinatio...
This paper studies face recognition and person-specific face image retrieval in unconstrained environments. The proposed method consists of two parts: offline and online learning....