Categorical semantics of a simple differential programming language
| Autor: | Dorette Pronk, Geoffrey Cruttwell, Jonathan Gallagher |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Structure (mathematical logic)
FOS: Computer and information sciences D.3.1 Computer Science - Programming Languages Computer science Automatic differentiation Programming language business.industry Computation Deep learning Mathematics - Category Theory Extension (predicate logic) computer.software_genre Operational semantics Simple (abstract algebra) TheoryofComputation_LOGICSANDMEANINGSOFPROGRAMS FOS: Mathematics Category Theory (math.CT) Artificial intelligence Differential (infinitesimal) business computer Programming Languages (cs.PL) |
| Popis: | With the increased interest in machine learning, and deep learning in particular, the use of automatic differentiation has become more wide-spread in computation. There have been two recent developments to provide the theoretical support for this types of structure. One approach, due to Abadi and Plotkin, provides a simple differential programming language. Another approach is the notion of a reverse differential category. In the present paper we bring these two approaches together. In particular, we show how an extension of reverse derivative categories models Abadi and Plotkin's language, and describe how this categorical model allows one to consider potential improvements to the operational semantics of the language. In Proceedings ACT 2020, arXiv:2101.07888 |
| Databáze: | OpenAIRE |
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