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 ...

The I-Con framework opens new avenues for AI discovery by organizing more than 20 ML algorithms into a unified structure, much like a periodic table for machine learning.

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.

MIT researchers have created a periodic table that shows how more than 20 classical machine-learning algorithms are connected. The new framework sheds light on how scientists could fuse strategies ...

In recent years, machine learning (ML) algorithms have proved themselves to be remarkably useful in helping people deal with different tasks: data classification and clustering, pattern revealing ...

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

'Periodic table of machine learning' could fuel AI discovery Researchers have created a unifying framework that can help scientists combine existing ideas to improve AI models or create new ones. ...