CSAIL researcher's machine-learning algorithm could help analyze flight delays & social networks.
March 4, 2014
CSAIL PI Alan Willsky and graduate student Ying Liu have developed a machine-learning algorithm that extends an artificial-intelligence technique to new tasks and could aid in the analysis of flight delays and social networks.
In a paper being presented in December at the annual conference of the Neural Information Processing Systems Foundation, MIT researchers describe a new technique that expands the class of data sets whose structure can be efficiently deduced. Not only that, but their technique naturally describes the data in a way that makes it much easier to work with.
In the paper, they apply their technique to several sample data sets, including information about commercial airline flights. Using only flights’ scheduled and actual departure times, the algorithm can efficiently infer vital information about the propagation of flight delays through U.S. airports. It also identifies those airports where delays are most likely to have far-reaching repercussions, which makes it simpler to reason about the behavior of the network as a whole.
More on MIT News: http://bit.ly/1f1qxRx