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» Coupling Two Complementary Knowledge Discovery Systems
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TSP
2010
14 years 4 months ago
Variance-component based sparse signal reconstruction and model selection
We propose a variance-component probabilistic model for sparse signal reconstruction and model selection. The measurements follow an underdetermined linear model, where the unknown...
Kun Qiu, Aleksandar Dogandzic
PPPJ
2009
ACM
15 years 4 months ago
Tracking performance across software revisions
Repository-based revision control systems such as CVS, RCS, Subversion, and GIT, are extremely useful tools that enable software developers to concurrently modify source code, man...
Nagy Mostafa, Chandra Krintz
GIS
2009
ACM
15 years 2 months ago
REG^2: a regional regression framework for geo-referenced datasets
Traditional regression analysis derives global relationships between variables and neglects spatial variations in variables. Hence they lack the ability to systematically discover...
Oner Ulvi Celepcikay, Christoph F. Eick
DIS
2006
Springer
14 years 11 months ago
Change Detection with Kalman Filter and CUSUM
Knowledge discovery systems are constrained by three main limited resources: time, memory and sample size. Sample size is traditionally the dominant limitation, but in many present...
Milton Severo, João Gama
ICRA
2005
IEEE
146views Robotics» more  ICRA 2005»
15 years 3 months ago
Probabilistic Gaze Imitation and Saliency Learning in a Robotic Head
— Imitation is a powerful mechanism for transferring knowledge from an instructor to a na¨ıve observer, one that is deeply contingent on a state of shared attention between the...
Aaron P. Shon, David B. Grimes, Chris Baker, Matth...