Efficient runtime verification for the Linux kernel
If safety-critical systems fail, they can cause significant damage, including loss of life. In this article we consider methods to verify their behavior in production.
Blocks, microworlds, puzzles, and adaptivity: teaching programming effectively
Bayesian statistical methods can make predictive data analysis more accurate. In this article, we evaluate possible solutions to the challenge of refining and increasing the value of high-volume data streams.
Sequential Monte Carlo for streaming data
Bayesian statistical methods can make predictive data analysis more accurate. In this article, we evaluate possible solutions to the challenge of refining and increasing the value of high-volume data streams.
When good models go bad: Minimizing dataset bias In AI
Sanjay Arora is a data scientist at Red Hat and a member of the Greater Boston Research Interest Group with particular interests in AI and machine learning. For RHRQ he interviewed Kate Saenko, a faculty member at Boston University and consulting professor for the MIT-IBM Watson AI Lab, about managing bias in machine learning datasets and the problems that remain unsolved.
Red Hat Research Days 2020—What are we thinking about now?
Highlights from the distributed workflows and infrastructure software tracks.