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16,279
Data Security
, 1979
"... The rising abuse of computers and increasing threat to personal privacy through data banks have stimulated much interest m the techmcal safeguards for data. There are four kinds of safeguards, each related to but distract from the others. Access controls regulate which users may enter the system and ..."
Abstract

Cited by 615 (3 self)
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and subsequently whmh data sets an active user may read or wrote. Flow controls regulate the dissemination of values among the data sets accessible to a user. Inference controls protect statistical databases by preventing questioners from deducing confidential information by posing carefully designed sequences
Sequential data assimilation with a nonlinear quasigeostrophic model using Monte Carlo methods to forecast error statistics
 J. Geophys. Res
, 1994
"... . A new sequential data assimilation method is discussed. It is based on forecasting the error statistics using Monte Carlo methods, a better alternative than solving the traditional and computationally extremely demanding approximate error covariance equation used in the extended Kalman filter. The ..."
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Cited by 800 (23 self)
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. A new sequential data assimilation method is discussed. It is based on forecasting the error statistics using Monte Carlo methods, a better alternative than solving the traditional and computationally extremely demanding approximate error covariance equation used in the extended Kalman filter
Behavior recognition via sparse spatiotemporal features
 In VSPETS
, 2005
"... A common trend in object recognition is to detect and leverage the use of sparse, informative feature points. The use of such features makes the problem more manageable while providing increased robustness to noise and pose variation. In this work we develop an extension of these ideas to the spatio ..."
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Cited by 717 (4 self)
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A common trend in object recognition is to detect and leverage the use of sparse, informative feature points. The use of such features makes the problem more manageable while providing increased robustness to noise and pose variation. In this work we develop an extension of these ideas
The Skyline Operator
 IN ICDE
, 2001
"... We propose to extend database systems by a Skyline operation. This operation filters out a set of interesting points from a potentially large set of data points. A point is interesting if it is not dominated by any other point. For example, a hotel might be interesting for somebody traveling to Nass ..."
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Cited by 567 (3 self)
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We propose to extend database systems by a Skyline operation. This operation filters out a set of interesting points from a potentially large set of data points. A point is interesting if it is not dominated by any other point. For example, a hotel might be interesting for somebody traveling
Inverse Acoustic and Electromagnetic Scattering Theory, Second Edition
, 1998
"... Abstract. This paper is a survey of the inverse scattering problem for timeharmonic acoustic and electromagnetic waves at fixed frequency. We begin by a discussion of “weak scattering ” and Newtontype methods for solving the inverse scattering problem for acoustic waves, including a brief discussi ..."
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Cited by 1061 (45 self)
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discussion of Tikhonov’s method for the numerical solution of illposed problems. We then proceed to prove a uniqueness theorem for the inverse obstacle problems for acoustic waves and the linear sampling method for reconstructing the shape of a scattering obstacle from far field data. Included in our
FastSLAM: A Factored Solution to the Simultaneous Localization and Mapping Problem
 In Proceedings of the AAAI National Conference on Artificial Intelligence
, 2002
"... The ability to simultaneously localize a robot and accurately map its surroundings is considered by many to be a key prerequisite of truly autonomous robots. However, few approaches to this problem scale up to handle the very large number of landmarks present in real environments. Kalman filterbase ..."
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Cited by 599 (10 self)
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based algorithms, for example, require time quadratic in the number of landmarks to incorporate each sensor observation. This paper presents FastSLAM, an algorithm that recursively estimates the full posterior distribution over robot pose and landmark locations, yet scales logarithmically with the number
Robust Monte Carlo Localization for Mobile Robots
, 2001
"... Mobile robot localization is the problem of determining a robot's pose from sensor data. This article presents a family of probabilistic localization algorithms known as Monte Carlo Localization (MCL). MCL algorithms represent a robot's belief by a set of weighted hypotheses (samples), whi ..."
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Cited by 839 (85 self)
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Mobile robot localization is the problem of determining a robot's pose from sensor data. This article presents a family of probabilistic localization algorithms known as Monte Carlo Localization (MCL). MCL algorithms represent a robot's belief by a set of weighted hypotheses (samples
Globus: A Metacomputing Infrastructure Toolkit
 International Journal of Supercomputer Applications
, 1996
"... Emerging highperformance applications require the ability to exploit diverse, geographically distributed resources. These applications use highspeed networks to integrate supercomputers, large databases, archival storage devices, advanced visualization devices, and/or scientific instruments to for ..."
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Cited by 1929 (51 self)
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to form networked virtual supercomputers or metacomputers. While the physical infrastructure to build such systems is becoming widespread, the heterogeneous and dynamic nature of the metacomputing environment poses new challenges for developers of system software, parallel tools, and applications
A discriminatively trained, multiscale, deformable part model
 In IEEE Conference on Computer Vision and Pattern Recognition (CVPR2008
, 2008
"... This paper describes a discriminatively trained, multiscale, deformable part model for object detection. Our system achieves a twofold improvement in average precision over the best performance in the 2006 PASCAL person detection challenge. It also outperforms the best results in the 2007 challenge ..."
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Cited by 555 (11 self)
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training. We combine a marginsensitive approach for data mining hard negative examples with a formalism we call latent SVM. A latent SVM, like a hidden CRF, leads to a nonconvex training problem. However, a latent SVM is semiconvex and the training problem becomes convex once latent information
Distance metric learning, with application to clustering with sideinformation,”
 in Advances in Neural Information Processing Systems 15,
, 2002
"... Abstract Many algorithms rely critically on being given a good metric over their inputs. For instance, data can often be clustered in many "plausible" ways, and if a clustering algorithm such as Kmeans initially fails to find one that is meaningful to a user, the only recourse may be for ..."
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Cited by 818 (13 self)
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Abstract Many algorithms rely critically on being given a good metric over their inputs. For instance, data can often be clustered in many "plausible" ways, and if a clustering algorithm such as Kmeans initially fails to find one that is meaningful to a user, the only recourse may
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