Searching for "Comment on "Finite sample performance guarantees of fusers for function estimators" [Information Fusion 1 35-44 (2000)]." – sorted by Relevance.
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On Optimal Projective Fusers For Function Estimators
- the problem of estimating a function f : ! d 7! [0; 1] based on a sample (X 1 ; f(X 1 )), (X 2 ; f(X 2
- Cited by 3 (3 self) – Add To MetaCart
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Multisensor Fusion Under Unknown Distributions - Finite-Sample Performance Guarantees
- Chapter 1 MULTISENSOR FUSION UNDER UNKNOWN DISTRIBUTIONS Finite-Sample Performance Guarantees
- Cited by 4 (3 self) – Add To MetaCart
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A generic sensor fusion problem: Classification and function estimation
- guaranteed to perform at least as good as the best classifier. The projective fusers for function estimators
- Cited by 2 (0 self) – Add To MetaCart
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Performance guarantees for regularized maximum entropy density estimation
- . Performance Guarantees for Regularized Maximum Entropy Density Estimation Miroslav Dudík 1 , Steven J
- Cited by 23 (5 self) – Add To MetaCart
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Efficient verification of performability guarantees
- bound on the cumulative distribution function (CDF) of the performance metric. Figure 1 shows a
- Cited by 1 (0 self) – Add To MetaCart
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Efficient Verification of Performability Guarantees
- bound on the cumulative distribution function (CDF) of the performance metric. Figure 1 shows a
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Estimation Of The Sample Size And Coverage For Guaranteed-Coverage Nonnormal Tolerance Intervals
- (⋅) is the density function of C. Hence, the estimator α ∧ always converges at rate O(1 m ). 3.2 Computing the Sample
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Projective Method For Generic Sensor Fusion Problem
- as the best fuser. Open issues in the fuser design are the finite sample performance and computational
- Cited by 1 (1 self) – Add To MetaCart
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Performance Guarantees for RegularizedMaximum Entropy Density Estimation
- . Performance Guarantees for RegularizedMaximum Entropy Density Estimation Miroslav Dud'ik1, Steven J. Phillips
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Variance Estimation for the Finite Population Distribution Function With Complete Auxiliary
- . INTRODUCTION The use of auxiliary information in estimating the finite population distribution function has
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