Certainty from uncertainty
نویسندگان
چکیده
منابع مشابه
The Certainty of Uncertainty
I believe that industry requirements for software estimate accuracy are infeasible. This is because software development, like economics and management science, is a complex, non-linear adaptive system and as such any attempt to estimate project effort or timescales is likely to result in very inaccurate estimates. In my view, it is important to understand the nature of the uncertainty in estim...
متن کاملThe certainty of uncertainty.
Uncertainty of measurement comprises, in general, many components. Some of these components may be evaluated from the statistical distribution of the results of a series of measurements and can be characterized by experimental standard deviations. The other components, which also can be characterized by standard deviations, are evaluated from assumed probability distributions based on experienc...
متن کاملExtracting Certainty from Uncertainty: Transductive Pairwise Classification from Pairwise Similarities
In this work, we study the problem of transductive pairwise classification from pairwise similarities 1. The goal of transductive pairwise classification from pairwise similarities is to infer the pairwise class relationships, to which we refer as pairwise labels, between all examples given a subset of class relationships for a small set of examples, to which we refer as labeled examples. We pr...
متن کامل“ Certainty Equivalence ” and “ Model Uncertainty ”
Simon’s and Theil’s certainty equivalence property justifies a convenient algorithm for solving dynamic programming problems with quadratic objectives and linear transition laws: first, optimize under perfect foresight, then substitute optimal forecasts for unknown future values. A similar decomposition into separate optimization and forecasting steps prevails when a decision maker wants a deci...
متن کامل“ Certainty Equivalence ” and “ Model Uncertainty ” Lars
Simon’s and Theil’s certainty equivalence property justifies a convenient algorithm for solving dynamic programming problems with quadratic objectives and linear transition laws: first, optimize under perfect foresight, then substitute optimal forecasts for unknown future values. A similar decomposition into separate optimization and forecasting steps prevails when a decision maker wants a deci...
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ژورنال
عنوان ژورنال: Nature
سال: 1993
ISSN: 0028-0836,1476-4687
DOI: 10.1038/362694a0