Most machine learning algorithms demand a huge number of matrix multiplications and other mathematical operations to process. The computational technology to manage these calculations didn’t ...

Specialization: Machine LearningInstructor: Geena Kim, Assistant Teaching ProfessorPrior knowledge needed: Calculus, Linear algebra, PythonLearning Outcomes Explain what unsupervised learning is, and ...

Machine learning uses algorithms to turn a data set into a model that can identify patterns or make predictions from new data. Which algorithm works best depends on the problem.

We sought to leverage machine learning to recognize and generalize patterns in 3D tensors, then use the trained ‘agent’ to find efficient decompositions of the matrix-multiplication tensor.

However, machine learning can be used to automate this process by training algorithms to identify defects from images or other data sources.

Characteristic fingerprint This algorithm is fairly widely employed in image and music analysis, as well as in other areas of machine learning and big data, Gigan explains. It essentially tries to ...

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

In this paper a Machine Learning algorithm is used to assist randomized techniques to compress the Method of Moments linear system matrix when analyzing electromagnetic scattering problems modeled ...

A new research paper titled “Discovering faster matrix multiplication algorithms with reinforcement learning” was published by researchers at DeepMind. “Here we report a deep reinforcement learning ...