TL;DR In our NeurIPS workshop paper , we analyze different performance measures for the evaluation of RNA secondary structure prediction algorithms, showing that commonly used measures are flawed in certain settings. We then propose the Weisfeiler-Lehman graph kernel as a competent measure for performance assessment in the field. RNA Secondary Structure Prediction Ribonucleic acid (RNA) […]

Reinforcement learning (RL) has shown impressive results in a variety of applications. Well known examples include game and video game playing, robotics and, recently, “Autonomous navigation of stratospheric balloons”. A lot of the successes came about by combining the expressiveness of deep learning with the power of RL. Already on their own though, both frameworks […]

By In reinforcement learning (RL), one of the major machine learning (ML) paradigms, an agent interacts with an environment. How well an RL agent can solve a problem, can be sensitive to choices such as the policy network architecture, the training hyperparameters, or the specific dynamics of the environment. A common strategy to deal with […]