Learning a Meta-Solver for Syntax-Guided Program Synthesis
Learning a Meta-Solver for Syntax-Guided Program Synthesis
复制标题
DOI：
--
复制
发表时间：
2018-09
期刊：
影响因子：
--
通讯作者：
X. Si;Yuan Yang;H. Dai;M. Naik;Le Song
中科院分区：
文献类型：
--
作者：
X. Si;Yuan Yang;H. Dai;M. Naik;Le Song
具有丰富语义的结构化数据的表示和转移学习是我们的工作。使用不同的语法G和语义φ？
Representation learning and transfer learning of structured data with rich semantics remain open problems. Our work addresses two fundamental challenges in this area: q How to learn a neural representation of both syntax and semantic constraints? q How to learn a transferable policy for program synthesis tasks with different syntax G and semantic φ? Cryptographic circuits synthesis Synthesize programs using a grammar adaptive policy network Jointly learn the representation of syntax and semantics