, deployment, and operation of a massive-scale machine learning system for targeted display advertising. Notably, the machine … learning system itself is deployed and has been in continual use for years, for thousands of advertising campaigns (in contrast … learning tasks, and then transferred to the target task. We present the design of this multistage transfer learning system …

Differential machine learning combines automatic adjoint differentiation (AAD) with modern machine learning (ML) in the … of supervised learning, where ML models are trained on examples of not only inputs and labels but also differentials of … regulations like XVA, CCR, FRTB or SIMM-MVA. TensorFlow implementation is available on https://github.com/differential-machine-learning …

Machine learning is an increasingly important and controversial topic in quantitative finance. A lively debate persists … as to whether machine learning techniques can be practical investment tools. Although machine learning algorithms can … a simple example of how investors can use machine learning techniques to forecast the cross-section of stock returns …

We give an explicit algorithm and source code for constructing risk models based on machine learning techniques. The … learning risk models to other constructions, including statistical risk models, risk models based on fundamental industry …