The goal in domain adaptation is to train a model using labeled data sampled from a domain different from the target domain on which the model will be deployed. We exploit unlabel...
There has been a recent, growing interest in classification and link prediction in structured domains. Methods such as conditional random fields and relational Markov networks sup...
Coreference analysis, also known as record linkage or identity uncertainty, is a difficult and important problem in natural language processing, databases, citation matching and m...
We describe an unsupervised method to segment objects detected in images using a novel variant of an interest point template, which is very efficient to train and evaluate. Once a...
Himanshu Arora, Nicolas Loeff, David A. Forsyth, N...
The ability to find tables and extract information from them is a necessary component of many information retrieval tasks. Documents often contain tables in order to communicate d...