论文标题
涉及期望的特殊功能的自动伴随分化
Automatic Adjoint Differentiation for special functions involving expectations
论文作者
论文摘要
我们解释了如何计算表单的功能梯度$ g = \ frac {1} {2} \ sum_ {i = 1}^{m}（e y_i -c_i）^2 $，通常在随机模型的校准中出现，使用自动伴随差异分化和平行化。我们扩展了Arxiv：1901.04200的工作，并更易于实施方法。我们还提供了我们的方法的实施，并应用了该技术来校准欧洲选择。
We explain how to compute gradients of functions of the form $G = \frac{1}{2} \sum_{i=1}^{m} (E y_i - C_i)^2$, which often appear in the calibration of stochastic models, using Automatic Adjoint Differentiation and parallelization. We expand on the work of arXiv:1901.04200 and give faster and easier to implement approaches. We also provide an implementation of our methods and apply the technique to calibrate European options.
