We generalise the problem of inverse reinforcement learning to multiple tasks, from multiple demonstrations. Each one may represent one expert trying to solve a different task, or ...
—With the exponential growth in the amount of data that is being generated in recent years, there is a pressing need for applying machine learning algorithms to large data sets. ...
Abstract—In this paper, we introduce FlowSifter, a systematic framework for online application protocol field extraction. FlowSifter introduces a new grammar model Counting Regu...
Chad R. Meiners, Eric Norige, Alex X. Liu, Eric To...
In this paper, we investigate a problem of predicting what images are likely to appear on the Web at a future time point, given a query word and a database of historical image str...
Scene text recognition has gained significant attention from the computer vision community in recent years. Recognizing such text is a challenging problem, even more so than the ...