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We study the problem of learning differentiable functions expressed as programs in a domain-specific language.
The heuristic search under conditions of error
Larry R Harris · 1974
Earlier work this paper cites.
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A Bagchi and A Mahanti · 1983
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Judea Pearl · 1984
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A new admissible heuristic for minimal-cost proofs
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The formal semantics of programming languages: an introduction
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Recent progress in the design and analysis of admissible heuristic functions
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Introduction to automata theory, languages, and computation, 3rd Edition
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David Sontag, Talya Meltzer, Amir Globerson, Tommi S Jaakkola, and Yair Weiss · 2012
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Using alternative suboptimality bounds in heuristic search
Richard Anthony Valenzano, Shahab Jabbari Arfaee, Jordan Thayer, Roni Stern, and Nathan R Sturtevant · 2013
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Syntax-guided synthesis
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Unsupervised learning by program synthesis
Kevin Ellis, Armando Solar-Lezama, and Joshua B. Tenenbaum · 2015
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Differentiable programs with neural libraries
Alexander L Gaunt, Marc Brockschmidt, Nate Kushman, and Daniel Tarlow · 2017
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Barret Zoph and Quoc V. Le · 2017
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Leveraging grammar and reinforcement learning for neural program synthesis
Rudy Bunel, Matthew Hausknecht, Jacob Devlin, Rishabh Singh, and Pushmeet Kohli · 2018
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Learning to infer graphics programs from hand-drawn images
Kevin Ellis, Daniel Ritchie, Armando Solar-Lezama, and Josh Tenenbaum · 2018
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Synthesizing programs for images using reinforced adversarial learning
Yaroslav Ganin, Tejas Kulkarni, Igor Babuschkin, S. M. Ali Eslami, and Oriol Vinyals · 2018
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Near code repository
Ameesh Shah, Eric Zhan, and Jennifer Sun · 2020
Closest in time.