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» On Computing Functions with Uncertainty
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ICCV
2007
IEEE
14 years 9 months ago
Active Learning with Gaussian Processes for Object Categorization
Discriminative methods for visual object category recognition are typically non-probabilistic, predicting class labels but not directly providing an estimate of uncertainty. Gauss...
Ashish Kapoor, Kristen Grauman, Raquel Urtasun, Tr...
CDC
2008
IEEE
109views Control Systems» more  CDC 2008»
14 years 2 months ago
Sensitivity analysis and computational uncertainty with applications to control of nonlinear parabolic partial differential equa
— In this paper we illustrate how sensitivities can be used to provide a practical precursor to dynamic transitions and numerical uncertainty in parameterized nonlinear parabolic...
John A. Burns, Lisa G. Davis
ISIPTA
1999
IEEE
169views Mathematics» more  ISIPTA 1999»
13 years 11 months ago
Dempster-Belief Functions Are Based on the Principle of Complete Ignorance
This paper shows that a "principle of complete ignorance" plays a central role in decisions based on Dempster belief functions. Such belief functions occur when, in a fi...
Peter P. Wakker
ATAL
2004
Springer
14 years 27 days ago
Fitting and Compilation of Multiagent Models through Piecewise Linear Functions
Decision-theoretic models have become increasingly popular as a basis for solving agent and multiagent problems, due to their ability to quantify the complex uncertainty and prefe...
David V. Pynadath, Stacy Marsella
ECSQARU
2009
Springer
13 years 11 months ago
Different Representations of Fuzzy Vectors
Fuzzy vectors were introduced as a description of imprecise quantities whose uncertainty originates from vagueness, not from a probabilistic model. Support functions are a classica...
Jiuzhen Liang, Mirko Navara, Thomas Vetterlein