Dynamic Adaptive Network Intelligence

نویسندگان

  • Richard Searle
  • Megan Bingham-Walker
چکیده

Accurate representational learning of both the explicit and implicit relationships within data is critical to the ability of machines to perform more complex and abstract reasoning tasks. We describe the efficient weakly supervised learning of such inferences by our Dynamic Adaptive Network Intelligence (DANI) model. We report state-of-the-art results for DANI over question answering tasks in the bAbI dataset that have proved difficult for contemporary approaches to learning representation (Weston et al., 2015).

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عنوان ژورنال:
  • CoRR

دوره abs/1511.06379  شماره 

صفحات  -

تاریخ انتشار 2015