تقرير
Distilling Wikipedia mathematical knowledge into neural network models
العنوان: | Distilling Wikipedia mathematical knowledge into neural network models |
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المؤلفون: | Kim, Joanne T., Landajuela, Mikel, Petersen, Brenden K. |
المصدر: | 1st Mathematical Reasoning in General Artificial Intelligence Workshop, ICLR 2021 |
سنة النشر: | 2021 |
المجموعة: | Computer Science |
مصطلحات موضوعية: | Computer Science - Machine Learning, Computer Science - Artificial Intelligence |
الوصف: | Machine learning applications to symbolic mathematics are becoming increasingly popular, yet there lacks a centralized source of real-world symbolic expressions to be used as training data. In contrast, the field of natural language processing leverages resources like Wikipedia that provide enormous amounts of real-world textual data. Adopting the philosophy of "mathematics as language," we bridge this gap by introducing a pipeline for distilling mathematical expressions embedded in Wikipedia into symbolic encodings to be used in downstream machine learning tasks. We demonstrate that a $\textit{mathematical}$ $\textit{language}$ $\textit{model}$ trained on this "corpus" of expressions can be used as a prior to improve the performance of neural-guided search for the task of symbolic regression. Comment: 6 pages, 4 figures |
نوع الوثيقة: | Working Paper |
URL الوصول: | http://arxiv.org/abs/2104.05930 |
رقم الأكسشن: | edsarx.2104.05930 |
قاعدة البيانات: | arXiv |
الوصف غير متاح. |