Treating annotation as a data understanding problem, rather than a labeling workflow challenge, can systematically drive down error rates and reduce the time and cost of producing high-quality data ...

The study demonstrates machine learning's role in predicting compressive strength of rice husk ash concrete, aiding the shift ...

By using reinforcement learning, researchers train virtual agent to determine the best time to administer medication based on ...

What's the real value in AI tools — and what separates those who use them well from those who don't? Sam Ransbotham, host of ...

Yoshua Bengio, considered by many to be one of the godfathers of AI, has long been at the forefront of machine-learning ...

Monoclonal antibody (mAb) manufacturing must continually improve to keep up with increasing demands. To do this, biomanufacturers can deploy machine learning tools to augment traditional process ...

The project will build upon CSIRO’s expertise in the field of QML to develop new and innovative QML models. QML has the potential to offer enhanced reliability, training speed-up and unique feature ...

Osaka Metropolitan University researchers developed a technique to improve machine learning reliability and estimation results of gravitational wave parameters.

In both cases, it would be better to train the machine learning model with a loss function that ignores the human’s objective and then adjust predictions ex post according to that objective. We ...

Machine learning is the ability of a machine to improve its performance based on previous results. Machine learning methods enable computers to learn without being explicitly programmed and have ...

We show that, compared with surgeon predictions and existing risk-prediction tools, our machine-learning model can enhance ...