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SpaceEfficient Estimation of Statistics over SubSampled Streams ABSTRACT
"... In many stream monitoring situations, the data arrival rate is so high that it is not even possible to observe each element of the stream. The most common solution is to sample a small fraction of the data stream and use the sample to infer properties and estimate aggregates of the original stream. ..."
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Cited by 2 (2 self)
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In many stream monitoring situations, the data arrival rate is so high that it is not even possible to observe each element of the stream. The most common solution is to sample a small fraction of the data stream and use the sample to infer properties and estimate aggregates of the original stream
Hierarchical Modelling and Analysis for Spatial Data. Chapman and Hall/CRC,
, 2004
"... Abstract Often, there are two streams in statistical research one developed by practitioners and other by main stream statisticians. Development of geostatistics is a very good example where pioneering work under realistic assumptions came from mining engineers whereas it is only now that statisti ..."
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Cited by 442 (45 self)
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Abstract Often, there are two streams in statistical research one developed by practitioners and other by main stream statisticians. Development of geostatistics is a very good example where pioneering work under realistic assumptions came from mining engineers whereas it is only now
Maintaining Stream Statistics over Sliding Windows (Extended Abstract)
, 2002
"... We consider the problem of maintaining aggregates and statistics over data streams, with respect to the last N data elements seen so far. We refer to this model as the sliding window model. We consider the following basic problem: Given a stream of bits, maintain a count of the number of 1's i ..."
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Cited by 269 (9 self)
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We consider the problem of maintaining aggregates and statistics over data streams, with respect to the last N data elements seen so far. We refer to this model as the sliding window model. We consider the following basic problem: Given a stream of bits, maintain a count of the number of 1&apos
Spaceefficient estimation of robust statistics and distribution testing
 In ICS
, 2010
"... Abstract: The generic problem of estimation and inference given a sequence of i.i.d. samples has been extensively studied in the statistics, property testing, and learning communities. A natural quantity of interest is the sample complexity of the particular learning or estimation problem being cons ..."
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Cited by 5 (1 self)
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sequence of i.i.d. samples. Robust statistics are a particularly interesting class of statistics in our setting because, by definition, they are resilient to noise or errors in the sampled data. We show that this property is enough to ensure that very spaceefficient stream algorithms exist
Frequency estimation of internet packet streams with limited space
 IN PROCEEDINGS OF THE 10TH ANNUAL EUROPEAN SYMPOSIUM ON ALGORITHMS
, 2002
"... We consider a router on the Internet analyzing the statistical properties of a TCP/IP packet stream. A fundamental difficulty with measuring traffic behavior on the Internet is that there is simply too much data to be recorded for later analysis, on the order of gigabytes a second. As a result, net ..."
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Cited by 168 (1 self)
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We consider a router on the Internet analyzing the statistical properties of a TCP/IP packet stream. A fundamental difficulty with measuring traffic behavior on the Internet is that there is simply too much data to be recorded for later analysis, on the order of gigabytes a second. As a result
A levelset approach to 3d reconstruction from range data
 International Journal of Computer Vision
, 1998
"... This paper presents a method that uses the level sets of volumes to reconstruct the shapes of 3D objects from range data. The strategy is to formulate 3D reconstruction as a statistical problem: find that surface which is mostly likely, given the data and some prior knowledge about the application d ..."
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Cited by 195 (24 self)
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natural scale space for hierarchical representations. This paper builds on previous work in both 3D reconstruction and levelset modeling. It presents a fundamental result in surface estimation from range data: an analytical characterization of the surface that maximizes the posterior probability. It also
The Limit of FiniteSample Size and a Problem with Subsampling
, 2007
"... This paper considers inference based on a test statistic that has a limit distribution that is discontinuous in a nuisance parameter or the parameter of interest. The paper shows that subsample, bn <nbootstrap, and standard fixed critical value tests based on such a test statistic often have asym ..."
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Cited by 12 (3 self)
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This paper considers inference based on a test statistic that has a limit distribution that is discontinuous in a nuisance parameter or the parameter of interest. The paper shows that subsample, bn <nbootstrap, and standard fixed critical value tests based on such a test statistic often have
Coil sensitivity encoding for fast MRI. In:
 Proceedings of the ISMRM 6th Annual Meeting,
, 1998
"... New theoretical and practical concepts are presented for considerably enhancing the performance of magnetic resonance imaging (MRI) by means of arrays of multiple receiver coils. Sensitivity encoding (SENSE) is based on the fact that receiver sensitivity generally has an encoding effect complementa ..."
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Cited by 193 (3 self)
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the number of kspace samples is reduced is referred to as the reduction factor R. In standard Fourier imaging, reducing the sampling density results in the reduction of the FOV, causing aliasing. In fact, SENSE reconstruction in the Cartesian case is efficiently performed by first creating one such aliased
Processing Set Expressions over Continuous Update Streams
, 2003
"... There is growing interest in algorithms for processing and querying continuous data streams (i.e., data that is seen only once in a fixed order) with limited memory resources. In its most general form, a data stream is actually an update stream, i.e., comprising dataitem deletions as well as insert ..."
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Cited by 64 (15 self)
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on the special case of insertonly streams and specic operators (e.g., union). In this paper, we propose the first spaceefficient algorithmic solution for estimating the cardinality of full
edged set expressions over general update streams. Our estimation algorithms are probabilistic in nature and rely on a
Random sampling techniques for space efficient online computation of order statistics of large datasets
 IN ACM SIGMOD '99
, 1999
"... In a recent paper [MRL98], we had described a general framework for single pass approximate quantile nding algorithms. This framework included several known algorithms as special cases. We had identi ed a new algorithm, within the framework, which had a signi cantly smaller requirement for main memo ..."
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Cited by 101 (1 self)
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is an extreme value (e.g., within the top 1 % of the elements), the space requirements of currently known algorithms are overly pessimistic. We provide a simple algorithm which estimates extreme values using less space than required by the earlier more general technique for computing all quantiles. Our
Results 1  10
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731