This paper deals with the problem of recognizing and extracting acronymdefinition pairs in Swedish medical texts. This project applies a rule-based method to solve the acronym rec...
In this paper we embed evolutionary computation into statistical learning theory. First, we outline the connection between large margin optimization and statistical learning and s...
We present a novel Evaluation Metric for Morphological Analysis (EMMA) that is both linguistically appealing and empirically sound. EMMA uses a graphbased assignment algorithm, op...
Learning from imbalanced datasets presents a convoluted problem both from the modeling and cost standpoints. In particular, when a class is of great interest but occurs relatively...
Nitesh V. Chawla, David A. Cieslak, Lawrence O. Ha...
Conditional random fields(CRFs) are a class of undirected graphical models which have been widely used for classifying and labeling sequence data. The training of CRFs is typicall...
Minmin Chen, Yixin Chen, Michael R. Brent, Aaron E...