Probabilistic programming has emerged as a powerful paradigm that integrates uncertainty directly into computational models. By embedding probabilistic constructs into conventional programming ...
The basic problem of a theory of truth approximation is defining when a theory is “close to the truth” about some relevant domain. Existing accounts of truthlikeness or verisimilitude address this ...
In this article we present applications of smooth numbers to the unconditional derandomization of some well-known integer factoring algorithms. We begin with Pollard's p – 1 algorithm, which finds in ...
Acxiom’s data onboarder LiveRamp hopes to solve the thorny problem of identity – thorny because consumers have thousands of different identifiers. LiveRamp – which Acxiom now refers to as its ...
This article is sponsored by Eyeota. The United States stands alone when it comes to its insistence on a predominantly deterministic approach to data-driven marketing. Because of that, the ongoing ...
As researchers around the world continue their long and arduous pursuit toward quantum computing, some are working on what might be considered “bridge” technologies to increase energy efficiency by ...
In this special guest feature, Matt Graves, Chief Data Officer at Infogroup, discusses how marketers can expand their target audiences and bridge the gap between business and consumer data through the ...
A photograph of the developed prototype. The system is designed such that the spintronic probabilistic bit comprising a stochastic magnetic tunnel junction (MTJ) [left] generates a physical random ...
Forbes contributors publish independent expert analyses and insights. I write about how to drive more value with data and analytics. This article is more than 9 years old. In a recent global survey of ...
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