A study led by UC Riverside researchers offers a practical fix to one of artificial intelligence's toughest challenges by ...

Abstract: In this paper, historical weather measurements and historical weather forecasts are compared for the purpose of training a machine learning model for predicting solar power plant production.

Enterprises have been piloting and testing different AI tools for the past few years to figure out what their adoption strategy will look like. Investors think that period of experimentation is coming ...

Infeasible paths constitute a bottleneck for the complete automation of software testing, one of the most expensive activities of software quality assurance. Research efforts have been spent on ...

Abstract: With the purpose of managing efficiency in a large number of published vulnerabilities, the time-intensive process requires significant effort and efficient vulnerability prioritization ...