Analysis-Driven Design of Representations For Sensing-Action Systems
Technical Report,26 Sep 2011,30 Jun 2017
University of California, Los Angeles Los Angeles United States
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We have developed what is, to the best of our knowledge, the first complete theory of representation for decision and control task, which has shown not only to encompass and explain all known phenomenology in deep neural network-based representation learning, but also to predict phenomena that were thus far unexplained.
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