Science, engineering, and industry are being transformed through the use of artificial intelligence and machine learning techniques and principles. The Master of Science in Machine Learning uses a ...

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

As organizations worldwide adopt machine learning across virtually every industry, the demand for machine learning engineers is on the rise.

Neuromorphic devices and circuits, and brain-inspired architectures and algorithms for energy-efficient AI. Tensor-methods for deep learning and tensor analysis of big and multi-modal data.

After uncovering a unifying algorithm that links more than 20 common machine-learning approaches, researchers organized them into a 'periodic table of machine learning' that can help scientists ...

Data engineers are responsible for the management of data infrastructure, the delivery of large-scale data processing and the preparation of datasets for analysis.

Systems controlled by next-generation computing algorithms could give rise to better and more efficient machine learning products, a new study suggests.

Our contributions include classification and introduction to the relevant fields of machine learning, a comprehensive and critical overview of machine learning usage in hardware security, and an ...

Machine Learning at CU Boulder Welcome to the hub for research in machine learning! Devoted to faculty and students that are interested in developing new machine learning algorithms and techniques, ...

The team found that this transfer of learning between the physics model and machine learning algorithm not only improves accuracy, but also happens in just a few seconds, significantly cutting down ...

Machine learning is an integral part of high stakes decision making in a broad swath of human-computer interactions. You apply for a job. You submit a loan application. Algorithms determine who ...