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» Modular Competitiveness for Distributed Algorithms
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ICCV
2009
IEEE
14 years 7 months ago
Realtime background subtraction from dynamic scenes
This paper examines the problem of moving object detection. More precisely, it addresses the difficult scenarios where background scene textures in the video might change over tim...
Li Cheng, Minglun Gong
AGI
2011
14 years 1 months ago
Comparing Humans and AI Agents
Comparing humans and machines is one important source of information about both machine and human strengths and limitations. Most of these comparisons and competitions are performe...
Javier Insa-Cabrera, David L. Dowe, Sergio Espa&nt...
STOC
2005
ACM
129views Algorithms» more  STOC 2005»
15 years 10 months ago
Learning with attribute costs
We study an extension of the "standard" learning models to settings where observing the value of an attribute has an associated cost (which might be different for differ...
Haim Kaplan, Eyal Kushilevitz, Yishay Mansour
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
81
Voted
SPLC
2008
14 years 11 months ago
Filtered Cartesian Flattening: An Approximation Technique for Optimally Selecting Features while Adhering to Resource Constraint
Software Product-lines (SPLs) use modular software components that can be reconfigured into different variants for different requirements sets. Feature modeling is a common method...
Jules White, B. Doughtery, Douglas C. Schmidt