We describe an efficient technique to weigh word-based features in binary classification tasks and show that it significantly improves classification accuracy on a range of proble...
Justin Martineau, Tim Finin, Anupam Joshi, Shamit ...
Recently there has been significant interest in supervised learning algorithms that combine labeled and unlabeled data for text learning tasks. The co-training setting [1] applie...
In this work we try to bridge the gap often encountered by researchers who find themselves with few or no labeled examples from their desired target domain, yet still have access ...
Background: Many important high throughput projects use in situ hybridization and may require the analysis of images of spatial cross sections of organisms taken with cellular lev...
Manjunatha Jagalur, Chris Pal, Erik G. Learned-Mil...
We propose a novel method for identifying road vehicles between two non-overlapping cameras. The problem is formulated as a same-different classification problem: probability of t...