Machine learning for the masses

Jan 18, 2019

By UCLA Samueli Newsroom

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NSF grant to UCLA computer science professors Todd Millstein and Guy Van den Broeck will support research to democratize emerging AI-based technology.

Two computer scientists at the UCLA Samueli School of Engineering have received a four-year, $947,000 research grant from the National Science Foundation to make machine learning – a branch of artificial intelligence where computer programs learn and improve on their own – more widely available and easier to work with.

“Machine learning has been really successful in the past decade, leading to state-of-the-art techniques for language translation, face recognition and other compelling applications, but these advances have mainly come from experts with specialized knowledge at major technology companies and at universities,” said Todd Millstein, professor of computer science and the principal investigator on the research. “Our primary goal with this research is to democratize machine learning, so that programs that utilize it can be written by anyone.” 

Machine learning technologies are powered by probability models. They are used in a broad range of applications, such as personalizing recommendations on social media, making predictions in finance, or figuring out what certain genes do. Still, these advances are mostly custom-built by exclusive groups. A much wider adoption of machine learning, where coders don’t need to know the theory behind it but still build programs using it, has not yet happened.

To change that paradigm, the UCLA computer scientists combine two strengths to help make machine learning more accessible – Millstein brings expertise in software programming, and co-principal investigator Guy Van den Broeck, an assistant professor of computer science, specializes in artificial intelligence and its applications.

They are looking to develop the “lingua franca” for machine learning based on probabilistic programming languages, which automatically infer the chances that a certain scenario is possible.

“If we want other scientists, or the general public, including even high school students, to do machine learning, then we need to make it as easy to use as many of today’s popular programming languages,” Van den Broeck said. “That means that users should not have to worry about how to build their own programming languages, but instead be able to rely on easy-to-learn tools they can trust will work as intended.”

Millstein and Van den Broeck had already been collaborating on this line of research prior to the grant. They are co-advisors to UCLA graduate student Steven Holtzen, who has already authored several papers on the topic.

The grant will support computer science graduate students. Results from the study, including a new programming language, will be open source.

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UCLA Engineering