776 research outputs found
The fused Kolmogorov filter: A nonparametric model-free screening method
A new model-free screening method called the fused Kolmogorov filter is
proposed for high-dimensional data analysis. This new method is fully
nonparametric and can work with many types of covariates and response
variables, including continuous, discrete and categorical variables. We apply
the fused Kolmogorov filter to deal with variable screening problems emerging
from a wide range of applications, such as multiclass classification,
nonparametric regression and Poisson regression, among others. It is shown that
the fused Kolmogorov filter enjoys the sure screening property under weak
regularity conditions that are much milder than those required for many
existing nonparametric screening methods. In particular, the fused Kolmogorov
filter can still be powerful when covariates are strongly dependent on each
other. We further demonstrate the superior performance of the fused Kolmogorov
filter over existing screening methods by simulations and real data examples.Comment: Published at http://dx.doi.org/10.1214/14-AOS1303 in the Annals of
Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical
Statistics (http://www.imstat.org
Superradiantly stable non-extremal Reissner-Nordstrom black holes
The superradiant stability is investigated for non-extremal
Reissner-Nordstrom black hole. We use an algebraic method to demonstrate that
all non-extremal Reissner-Nordstrom black holes are superradiantly stable
against a charged massive scalar perturbation. This improves the results
obtained before for non-extremal Reissner-Nordstrom black holes
Bot Electioneering Volume: Visualizing Social Bot Activity During Elections
It has been widely recognized that automated bots may have a significant
impact on the outcomes of national events. It is important to raise public
awareness about the threat of bots on social media during these important
events, such as the 2018 US midterm election. To this end, we deployed a web
application to help the public explore the activities of likely bots on Twitter
on a daily basis. The application, called Bot Electioneering Volume (BEV),
reports on the level of likely bot activities and visualizes the topics
targeted by them. With this paper we release our code base for the BEV
framework, with the goal of facilitating future efforts to combat malicious
bots on social media.Comment: 3 pages, 3 figures. In submissio
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