We study the problem of selecting a subset of k random variables from a large set, in order to obtain the best linear prediction of another variable of interest. This problem can ...
—In this paper we investigate the local probability density function (pdf) of natural signals in sparse domains. The statistical properties of natural signals are characterized m...
We propose a driver risk evaluation method based on the analysis of driving data captured with drive recorders. To evaluate the acceleration behavior of each driver we plot the ma...
We develop a novel approach to the semantic analysis of short text segments and demonstrate its utility on a large corpus of Web search queries. Extracting meaning from short text...
While conventional wisdom holds that residential users experience a high degree of compromise and infection, this presumption has seen little validation in the way of an in-depth s...
Gregor Maier, Anja Feldmann, Vern Paxson, Robin So...