1.0Microsoft Researchhttps://www.microsoft.com/en-us/researchBen Ryonhttps://www.microsoft.com/en-us/research/people/v-beryonmicrosoft-com/New Meta-learning Techniques for Neural Program Inductionrich600338<blockquote class="wp-embedded-content" data-secret="BkE5NyX2VL"><a href="https://www.microsoft.com/en-us/research/blog/neural-program-induction/">New Meta-learning Techniques for Neural Program Induction</a></blockquote><iframe sandbox="allow-scripts" security="restricted" src="https://www.microsoft.com/en-us/research/blog/neural-program-induction/embed/#?secret=BkE5NyX2VL" width="600" height="338" title="“New Meta-learning Techniques for Neural Program Induction” — Microsoft Research" data-secret="BkE5NyX2VL" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"></iframe><script type="text/javascript">
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https://www.microsoft.com/en-us/research/wp-content/uploads/2017/12/Untitled-2-cr_edit5-2_1-655x280.jpg655280Much research in AI lately focuses on extending the capabilities of deep learning architectures: moving beyond simple classification and pattern recognition into the realm of learning algorithmic tasks, such as inductive programming. Building on our past work in neural program synthesis for learning string transformations in a functional language, our most recent work explores the […]