We present two studies that evaluate the accuracy of human responses to an intelligent agent’s data classification questions. Prior work has shown that agents can elicit accurat...
Understanding Internet access trends at a global scale, i.e., how people use the Internet, is a challenging problem that is typically addressed by analyzing network traces. However...
Ionut Trestian, Supranamaya Ranjan, Aleksandar Kuz...
We propose semantic texton forests, efficient and powerful new low-level features. These are ensembles of decision trees that act directly on image pixels, and therefore do not ne...
The discipline of narratology has long recognized the need to classify documents as instances of different text types. We have discovered that classification is as applicable to h...
We describe experimental results for unsupervised recognition of the textual contents of book-images using fully automatic mutual-entropy-based model adaptation. Each experiment s...