One of the current hot research topics is the combination of two of the most recent technological breakthroughs: machine ...

which improves standard Q-learning algorithm so that the proposed algorithm seeks for the optimal solution ensuring that the safety premise is satisfied. During the process of finding the solution in ...

Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge CB3 0AS, United Kingdom Cambridge Centre for Advanced Research and Education in Singapore, CARES Ltd., 1 CREATE ...

Then they trained a collection of machine learning surrogate models for each radiation detector and used an offline optimization algorithm to determine the voltage settings for reducing radiation ...

Typical Azure Machine Learning Project Lifecycle (source: Microsoft). In the Q&A that follows, Boyd shares what inspired ... AutoML in Azure ML automatically explores a range of algorithms and ...

We aimed to assess the association between deep learning-derived cardiac chamber volumes (right atrial, right ventricular, left ventricular, and left atrial) and mass (left ventricular) from these ...

Incorporating statistical inference in RL algorithms is essential for understanding and managing uncertainty in model performance. This paper introduces a generalized framework for time-varying ...