“This makes active-learning models very efficient at predicting performance.” Typically, Reker and other researchers apply active learning algorithms to generate new data for example to identify new ...

For deep active learning algorithms, on the other hand, there are four kinds of strategies: uncertainty-based, distribution-based, hybrid and automatically designed.

(4) an active-learning algorithm that improves on failed synthesis procedures. The study also revealed several opportunities to enhance the lab’s active-learning algorithm by addressing failures ...

Training machine learning models requires efficient learning algorithms that economise on the number of labelled data points used for training. In the active learning setting, the objective is to ...

The interaction of human psychology and algorithm amplification leads to dysfunction because social learning supports cooperation and problem-solving, but social media algorithms are designed to ...