Learning to Code: Machine Learning for Program Induction
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Learning to Code: Machine Learning for Program Induction
The task of synthesizing programs given only example input-output behaviour is experiencing a surge of interest in the machine learning community. We present two directions for applying machine learning ideas to this task. First we describe the TerpreT framework which uses end-to-end differentiable program interpreters and gradient descent to ...
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