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| Title | Academic presentation in China Guangzhou |
| Reporter | Hao Ni |
| Report Date | Dec 25 2017 |
| Report Address | South China University of Technology，Guangzhou，China |
| Report Title | The signature approach for the supervised learning problem on the path space and its application |
| Report Brief | Inspired by the rough paths theory (RPT) the core object of RPT – the so-called the signature of the path provides a good feature set for sequential data. In the talk, we discuss how to combine the recurrent neural network with the signature feature set to tackle the supervised learning problem on the path space, which is based on the theory of the solution to the stochastic differential equation (SDE). We will apply this method to learn the solution to unknown SDEs without any prior knowledge and demonstrate the effectiveness of this method. Finally we will discuss the potential applications of this method. |
| URL | Page Link |