Kim and his colleagues developed an offline algorithm that estimates min-entropy ... (Daegu Gyeongbuk Institute of Science and Technology). (2021, May 4). Algorithms improve how we protect our data.

People know that a more data-based, analytically driven, algorithm supported management process is required. They just want management to be smart about setting priorities and getting algorithms ...

The Case for Algorithm Driven: Understanding the advantage that algorithms have over static data in the wild is important. In fact, organizations can gain the upper hand by having an algorithm ...

No company or public institution is willing to publicize its data and algorithms for fear of being labeled racist or sexist, or maybe worse, having a great algorithm stolen by a competitor.

Look closely at any machine-learning algorithm and you’ll inevitably find people—people making choices about which data to gather and how to weigh it, choices about design and target variables.

Ying Zhang, Mortaza Jamshidian, On Algorithms for the Nonparametric Maximum Likelihood Estimator of the Failure Function with Censored Data, Journal of Computational and Graphical Statistics, Vol. 13, ...

This is what's important: machine-learning systems—"algorithms"—produce outputs that reflect the training data over time. If the inputs are biased (in the mathematical sense of the word), the ...