Data on modern networks are massive and are applied in the area of monitoring and analyzing activities at the network element, network-wide, and customer and service levels for a h...
Roland Heilmann, Daniel A. Keim, Christian Panse, ...
Reinforcement learning is an effective technique for learning action policies in discrete stochastic environments, but its efficiency can decay exponentially with the size of the ...
In visual processing the ability to deal with missing and noisy information is crucial. Occlusions and unreliable feature detectors often lead to situations where little or no dir...
With a focus on presenting information at the right time, the ubicomp community can benefit greatly from learning the most salient human measures of cognitive load. Cognitive load...
Eija Haapalainen, Seungjun Kim, Jodi Forlizzi, Ani...
Abstract Irregularities are widespread in large databases and often lead to erroneous conclusions with respect to data mining and statistical analysis. For example, considerable bi...
Siu-Tong Au, Rong Duan, Siamak G. Hesar, Wei Jiang