Tech Xplore on MSN
Mistaken correlations: Why it's critical to move beyond overly aggregated machine-learning metrics
MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data other than what they were trained on, raising questions about the need to ...
Tech Xplore on MSN
New method helps AI reason like humans without extra training data
A study led by UC Riverside researchers offers a practical fix to one of artificial intelligence's toughest challenges by ...
While experimentation is essential, traditional A/B testing can be excessively slow and expensive, according to DoorDash engineers Caixia Huang and Alex Weinstein. To address these limitations, they ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results