Much evidence has shown that prediction markets, when used in isolation, can effectively aggregate dispersed information about uncertain future events and produce remarkably accur...
Yiling Chen, Xi Alice Gao, Rick Goldstein, Ian A. ...
A common approach in machine learning is to use a large amount of labeled data to train a model. Usually this model can then only be used to classify data in the same feature spac...
Abstract. The prediction of diagnosis codes is typically based on freetext entries in clinical documents. Previous attempts to tackle this problem range from strictly rule-based sy...
Many data sets exist that contain both geospatial and temporal elements. Within such data sets, it can be difficult to determine how the data have changed over spatial and tempor...
Orland Hoeber, Garnett Carl Wilson, Simon Harding,...
In this paper, we consider the challenge of designing a reflective middleware to integrate multiple autonomous simulation models into an integrated simulation environment (multiasi...