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» Estimating Sum by Weighted Sampling
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ICALP
2007
Springer
13 years 11 months ago
Estimating Sum by Weighted Sampling
We study the classic problem of estimating the sum of n variables. The traditional uniform sampling approach requires a linear number of samples to provide any non-trivial guarante...
Rajeev Motwani, Rina Panigrahy, Ying Xu 0002
PODS
2005
ACM
151views Database» more  PODS 2005»
14 years 4 months ago
Estimating arbitrary subset sums with few probes
Suppose we have a large table T of items i, each with a weight wi, e.g., people and their salary. In a general preprocessing step for estimating arbitrary subset sums, we assign e...
Noga Alon, Nick G. Duffield, Carsten Lund, Mikkel ...
ISBI
2004
IEEE
14 years 5 months ago
Quantitative Imaging: How to Measure Size Features in Digitized Images
We present an nD image processing paradigm to obtain high precision estimates of geometric object properties such as volume, surface area, and length from digitized data. We prove...
Lucas J. van Vliet, Piet W. Verbeek, Ian T. Young
CSDA
2006
84views more  CSDA 2006»
13 years 4 months ago
Robust weighted LAD regression
The least squares linear regression estimator is well-known to be highly sensitive to unusual observations in the data, and as a result many more robust estimators have been propo...
Avi Giloni, Jeffrey S. Simonoff, Bhaskar Sengupta
DSMML
2004
Springer
13 years 10 months ago
Transformations of Gaussian Process Priors
Abstract. Gaussian process prior systems generally consist of noisy measurements of samples of the putatively Gaussian process of interest, where the samples serve to constrain the...
Roderick Murray-Smith, Barak A. Pearlmutter