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Measurement, Modeling, and Analysis of a PeertoPeer FileSharing Workload
, 2003
"... Peertopeer (P2P) file sharing accounts for an astonishing volume of current Internet tra#c. This paper probes deeply into modern P2P file sharing systems and the forces that drive them. By doing so, we seek to increase our understanding of P2P file sharing workloads and their implications for futu ..."
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Cited by 486 (7 self)
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Peertopeer (P2P) file sharing accounts for an astonishing volume of current Internet tra#c. This paper probes deeply into modern P2P file sharing systems and the forces that drive them. By doing so, we seek to increase our understanding of P2P file sharing workloads and their implications
Compressed sensing
 IEEE Trans. Inf. Theory
, 2006
"... We study the notion of Compressed Sensing (CS) as put forward in [14] and related work [20, 3, 4]. The basic idea behind CS is that a signal or image, unknown but supposed to be compressible by a known transform, (eg. wavelet or Fourier), can be subjected to fewer measurements than the nominal numbe ..."
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Cited by 3600 (24 self)
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number of pixels, and yet be accurately reconstructed. The samples are nonadaptive and measure ‘random ’ linear combinations of the transform coefficients. Approximate reconstruction is obtained by solving for the transform coefficients consistent with measured data and having the smallest possible `1
Inductive Learning Algorithms and Representations for Text Categorization
, 1998
"... Text categorization – the assignment of natural language texts to one or more predefined categories based on their content – is an important component in many information organization and management tasks. We compare the effectiveness of five different automatic learning algorithms for text categori ..."
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Cited by 641 (8 self)
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categorization in terms of learning speed, realtime classification speed, and classification accuracy. We also examine training set size, and alternative document representations. Very accurate text classifiers can be learned automatically from training examples. Linear Support Vector Machines (SVMs
Near Optimal Signal Recovery From Random Projections: Universal Encoding Strategies?
, 2004
"... Suppose we are given a vector f in RN. How many linear measurements do we need to make about f to be able to recover f to within precision ɛ in the Euclidean (ℓ2) metric? Or more exactly, suppose we are interested in a class F of such objects— discrete digital signals, images, etc; how many linear m ..."
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Cited by 1513 (20 self)
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Suppose we are given a vector f in RN. How many linear measurements do we need to make about f to be able to recover f to within precision ɛ in the Euclidean (ℓ2) metric? Or more exactly, suppose we are interested in a class F of such objects— discrete digital signals, images, etc; how many linear
Active Learning with Statistical Models
, 1995
"... For manytypes of learners one can compute the statistically "optimal" way to select data. We review how these techniques have been used with feedforward neural networks [MacKay, 1992# Cohn, 1994]. We then showhow the same principles may be used to select data for two alternative, statist ..."
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Cited by 677 (12 self)
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, statisticallybased learning architectures: mixtures of Gaussians and locally weighted regression. While the techniques for neural networks are expensive and approximate, the techniques for mixtures of Gaussians and locally weighted regression are both efficient and accurate.
TopicSensitive PageRank
, 2002
"... In the original PageRank algorithm for improving the ranking of searchquery results, a single PageRank vector is computed, using the link structure of the Web, to capture the relative "importance" of Web pages, independent of any particular search query. To yield more accurate search resu ..."
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Cited by 535 (10 self)
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In the original PageRank algorithm for improving the ranking of searchquery results, a single PageRank vector is computed, using the link structure of the Web, to capture the relative "importance" of Web pages, independent of any particular search query. To yield more accurate search
Integrating classification and association rule mining
 In Proc of KDD
, 1998
"... Classification rule mining aims to discover a small set of rules in the database that forms an accurate classifier. Association rule mining finds all the rules existing in the database that satisfy some minimum support and minimum confidence constraints. For association rule mining, the target of di ..."
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Cited by 561 (21 self)
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Classification rule mining aims to discover a small set of rules in the database that forms an accurate classifier. Association rule mining finds all the rules existing in the database that satisfy some minimum support and minimum confidence constraints. For association rule mining, the target
Timing Attacks on Implementations of DiffieHellman, RSA, DSS, and Other Systems
, 1996
"... By carefully measuring the amount of time required to perform private key operations, attackers may be able to find fixed DiffieHellman exponents, factor RSA keys, and break other cryptosystems. Against a vulnerable system, the attack is computationally inexpensive and often requires only known cip ..."
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Cited by 644 (3 self)
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ciphertext. Actual systems are potentially at risk, including cryptographic tokens, networkbased cryptosystems, and other applications where attackers can make reasonably accurate timing measurements. Techniques for preventing the attack for RSA and DiffieHellman are presented. Some cryptosystems will need
Marker tracking and HMD calibration for a videobased augmented reality conferencing system
 in The 2nd International Workshop on Augmented Reality (IWAR 99
, 1999
"... We describe an augmented reality conferencing system which uses the overlay of virtual images on the real world. Remote collaborators are represented on Virtual Monitors which can be freely positioned about a user in space. Users can collaboratively view and interact with virtual objects using a sha ..."
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Cited by 514 (26 self)
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shared virtual whiteboard. This is possible through precise virtual image registration using fast and accurate computer vision techniques and HMD calibration. We propose a method for tracking fiducial markers and a calibration method for optical seethrough HMD based on the marker tracking. 1.
Vivaldi: A Decentralized Network Coordinate System
 In SIGCOMM
, 2004
"... Largescale Internet applications can benefit from an ability to predict roundtrip times to other hosts without having to contact them first. Explicit measurements are often unattractive because the cost of measurement can outweigh the benefits of exploiting proximity information. Vivaldi is a simp ..."
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Cited by 593 (5 self)
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simple, lightweight algorithm that assigns synthetic coordinates to hosts such that the distance between the coordinates of two hosts accurately predicts the communication latency between the hosts.
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