Complex queries over high speed data streams often need to rely on approximations to keep up with their input. The research community has developed a rich literature on approximat...
Theodore Johnson, S. Muthukrishnan, Irina Rozenbau...
This work investigates the accuracy and efficiency tradeoffs between centralized and collective (distributed) algorithms for (i) sampling, and (ii) n-way data analysis techniques i...
Processing and extracting meaningful knowledge from count data is an important problem in data mining. The volume of data is increasing dramatically as the data is generated by da...
Reservoir sampling is a well-known technique for sequential random sampling over data streams. Conventional reservoir sampling assumes a fixed-size reservoir. There are situation...
Mohammed Al-Kateb, Byung Suk Lee, Xiaoyang Sean Wa...
Sensors capable of sensing phenomena at high data rates—on the order of tens to hundreds of thousands of samples per second—are useful in many industrial, civil engineering, s...
Lewis Girod, Yuan Mei, Ryan Newton, Stanislav Rost...