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» On Computing Functions with Uncertainty
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ICCV
2007
IEEE
16 years 1 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»
15 years 6 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»
15 years 4 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
15 years 5 months 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
15 years 3 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