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Modern recruiting is marked by an “algorithmic monoculture” in which only a small number of vendors supply applicant ...

The machine learning algorithm and subsequent simulations are fueled by data, expert knowledge and statistical models ...

Abstract: We propose new algorithms to achieve k-coverage in dense sensor networks. In such networks, covering sensor locations approximates covering the whole area. However, it has been shown before ...

Abstract: We study a class of random sampling-based algorithms for solving general non-differentiable optimization problems. These are iterative approaches that are based on sampling from and updating ...

In times past, when we wanted to know which team would win the World Cup, we had to turn to seers with crystal balls, use ...

Data science and machine learning algorithms can help us form probabilistic forecasts of things like sporting events.

A thought experiment in prevention: What if dogs do more for cardiovascular health than statins? Let’s examine the data, ...

Researchers have developed a quantum method to amplify less random numbers to certifiably random ones, enhancing digital ...

A recent study published in the Journal of Cultural Economics suggests that highly accurate content recommendation algorithms ...

For generations, agronomic knowledge has been produced on research stations like AU Flakkebjerg, where fields are designed to ...

The randomness in quantum physics is imperfect and needs amplification to be considered truly random, the researchers say.