The aim of our work is to provide support for reading (or skimming) scientific papers. In this paper we report on the task to identify concepts or terms with positive attributions ...
Traditional machine learning makes a basic assumption: the training and test data should be under the same distribution. However, in many cases, this identicaldistribution assumpt...
We propose a framework for large scale learning and annotation of structured models. The system interleaves interactive labeling (where the current model is used to semiautomate t...
Frequent episode discovery is a popular framework for mining data available as a long sequence of events. An episode is essentially a short ordered sequence of event types and the...
Srivatsan Laxman, P. S. Sastry, K. P. Unnikrishnan
We envision a future in which the global economy and the Internet will merge and evolve together into an information economy bustling with billions of economically motivated softw...
Jeffrey O. Kephart, James E. Hanson, Amy R. Greenw...