Postdoctoral Research Fellow

4 days ago


Umeå, Västerbotten, Sweden Euro Math Soc Full time
About the Project
Artificial intelligence (AI) has become ubiquitous in our daily lives, but we often overlook the technology being in action. Machine learning (ML) is an area at the technical core of AI, and deep neural networks (DNN) have achieved enormous success. However, the research focus of ML has shifted from pursuing high accuracy to other qualities of an ML system. One highly valued trait of an ML system is interpretability, which is essential for critical tasks where a black-box ML classifier is rejected even if it performs well on a test dataset.

The project aims to further develop Mixture of Linear Models (MLM) by incorporating more sophisticated region-specific models and enhancing the training of the modules in MLM. These improvements will expand the potential applications of the method and increase prediction accuracy. The successful candidate will contribute to the development of novel algorithms for interpretable ML and create a platform for a formal study of the relationship between interpretability and prediction accuracy.

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