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- January 28, 2012 4:56 pm: Will 2012 be the year of Big Data?
- August 14, 2011 10:41 pm: UK plans to exempt data mining from copyright laws
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- March 26, 2011 7:57 pm: How Kinect body tracking works and how Machine Learning helped
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Risk Assessment of Rare Events in adversarial Scenarios
The RAND corporation just published an interesting paper exploring the benefits of using risk prediction to reduce the screening required at airports. You might have noticed various attempts to establish some kind of fast-lane or trusted traveler program. Obvious this is a very sensitive topic and probably hard to get right. Screening certain groups of the population more than others (”profiling”) is generally frowned upon and also not a good idea in general (see “Strong profiling is not mathematically optimal for discovering rare malfeasors on rare event detection“), but what hasn’t been examined much is identifying people that can be considered more “safe” than others. The paper explores that idea and shows that even under the assumption that the bad guys will try and subvert this program that there can be benefits to implementing this solution. The paper is a bit sparse on mathematical details. Certainly an interesting idea, though.