When you listen to quantum enthusiasts, you may feel tempted to treat QML as an emerging silver bullet, which it isn’t.

Multi-target quantum compilation algorithm. Machine Learning: Science and Technology, 2024; 5 (4): 045057 DOI: 10.1088/2632-2153/ad9705 ...

MIT researchers designed a computationally efficient algorithm for machine learning with symmetric data that also requires fewer data for training than conventional approaches. Their work could inform ...

Algorithms, machine learning and artificial intelligence each play a crucial role in optimizing your hiring processes and keeping you competitive in the talent market.

Look closely at any machine-learning algorithm and you’ll inevitably find people—people making choices about which data to gather and how to weigh it, choices about design and target variables.

This pre-processing step is crucial for improving the efficiency and accuracy of classification algorithms, including but not limited to k-nearest neighbours, support vector machines, and ensemble ...

Psychological testing has evolved from Freud to AI and eye tracking. Technology adds depth, but theory and ethics must guide its use to ensure meaningful and equitable diagnoses.

Finding relationships between bio-signals and health outcomes is complicated for many reasons, including sorting out irrelevant data.