This new approach, published in Health Data Science, leverages advanced deep learning models to significantly improve segmentation accuracy, even when labeled data is scarce. MRI segmentation ...

Dr. James McCaffrey of Microsoft Research provides a code-driven tutorial on PUL problems, which often occur with security or medical data in cases like training a machine learning model to predict if ...

For example, if you want to automatically ... but it can be expensive to label it. Instead, researchers can use the unlabeled data as a warm-up for the machine-learning algorithm.

Supervised learning is defined by its use of labeled datasets to train algorithms ... demonstrates the potential of learning from unlabeled data. Microsoft is using unsupervised learning to ...

Industries from retail to finance are using clustering to personalize services, detect fraud, monitor equipment and improve ...

While prompting is seen as an error-prone process with limited quality gains, fine-tuning requires large amounts of human-labeled data which is ... based on past input examples alone, meaning ...