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Gradient projection for sparse reconstruction: Application to compressed sensing and other inverse problems
 IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING
, 2007
"... Many problems in signal processing and statistical inference involve finding sparse solutions to underdetermined, or illconditioned, linear systems of equations. A standard approach consists in minimizing an objective function which includes a quadratic (squared ℓ2) error term combined with a spa ..."
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Cited by 539 (17 self)
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sparsenessinducing (ℓ1) regularization term.Basis pursuit, the least absolute shrinkage and selection operator (LASSO), waveletbased deconvolution, and compressed sensing are a few wellknown examples of this approach. This paper proposes gradient projection (GP) algorithms for the bound
Loopy belief propagation for approximate inference: An empirical study. In:
 Proceedings of Uncertainty in AI,
, 1999
"... Abstract Recently, researchers have demonstrated that "loopy belief propagation" the use of Pearl's polytree algorithm in a Bayesian network with loops can perform well in the context of errorcorrecting codes. The most dramatic instance of this is the near Shannonlimit performanc ..."
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Cited by 676 (15 self)
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. Introduction The task of calculating posterior marginals on nodes in an arbitrary Bayesian network is known to be NP hard In this paper we investigate the approximation performance of "loopy belief propagation". This refers to using the wellknown Pearl polytree algorithm [12] on a Bayesian network
An Efficient Solution to the FivePoint Relative Pose Problem
, 2004
"... An efficient algorithmic solution to the classical fivepoint relative pose problem is presented. The problem is to find the possible solutions for relative camera pose between two calibrated views given five corresponding points. The algorithm consists of computing the coefficients of a tenth degre ..."
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Cited by 484 (13 self)
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in minimal as well as overdetermined cases. The performance is compared to that of the well known 8 and 7point methods and a 6point scheme. The algorithm is used in a robust hypothesizeandtest framework to estimate structure and motion in realtime with low delay. The realtime system uses solely visual
Automatic Programming of Behaviorbased Robots using Reinforcement Learning
, 1991
"... This paper describes a general approach for automatically programming a behaviorbased robot. New behaviors are learned by trial and error using a performance feedback function as reinforcement. Two algorithms for behavior learning are described that combine Q learning, a well known scheme for propa ..."
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Cited by 368 (17 self)
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This paper describes a general approach for automatically programming a behaviorbased robot. New behaviors are learned by trial and error using a performance feedback function as reinforcement. Two algorithms for behavior learning are described that combine Q learning, a well known scheme
Pivoted Document Length Normalization
 SIGIR'96
, 1996
"... Automatic information retrieval systems have to deal with documents of varying lengths in a text collection. Document length normalization is used to fairly retrieve documents of all lengths. In this study, we ohserve that a normalization scheme that retrieves documents of all lengths with similar c ..."
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Cited by 477 (16 self)
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collections, yielding a robust, collectzorz independent normalization technique. We use the idea of pivoting with the well known cosine normalization function. We point out some shortcomings of the cosine function and present two new normalization functions–pivoted unique normalization and piuotert byte size
A Fuzzy Commitment Scheme
 ACM CCS'99
, 1999
"... We combine wellknown techniques from the areas of errorcorrecting codes and cryptography to achieve a new type of cryptographic primitive that we refer to as a fuzzy commitment scheme. Like a conventional cryptographic commitment scheme, our fuzzy commitment scheme is both concealing and binding: i ..."
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Cited by 344 (1 self)
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We combine wellknown techniques from the areas of errorcorrecting codes and cryptography to achieve a new type of cryptographic primitive that we refer to as a fuzzy commitment scheme. Like a conventional cryptographic commitment scheme, our fuzzy commitment scheme is both concealing and binding
The Determinants of Credit Spread Changes.
 Journal of Finance
, 2001
"... ABSTRACT Using dealer's quotes and transactions prices on straight industrial bonds, we investigate the determinants of credit spread changes. Variables that should in theory determine credit spread changes have rather limited explanatory power. Further, the residuals from this regression are ..."
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Cited by 422 (2 self)
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grade bond yield changes on Treasury yield changes and stock returns (see Kwan (1996)) we find that the R 2 falls to five percent when the dependent variable is credit spread changes. Hence, while much is known about yield changes, we have very limited knowledge about the determinants of credit spread
Regularization Theory and Neural Networks Architectures
 Neural Computation
, 1995
"... We had previously shown that regularization principles lead to approximation schemes which are equivalent to networks with one layer of hidden units, called Regularization Networks. In particular, standard smoothness functionals lead to a subclass of regularization networks, the well known Radial Ba ..."
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Cited by 395 (32 self)
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We had previously shown that regularization principles lead to approximation schemes which are equivalent to networks with one layer of hidden units, called Regularization Networks. In particular, standard smoothness functionals lead to a subclass of regularization networks, the well known Radial
vic: A Flexible Framework for Packet Video
 ACM Multimedia
, 1995
"... The deployment of IP Multicast has fostered the development of a suite of applications, collectively known as the MBone tools, for realtime multimedia conferencingover the Internet. Two of these tools  nv from Xerox PARC and ivs from INRIA  provide video transmission using softwarebased codec ..."
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Cited by 369 (18 self)
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, and support for diverse compression algorithms. We also propose a novel compression scheme called "IntraH. 261". Created as a hybrid of the nv and ivs codecs, IntraH. 261 provides a factor of 23 improvement in compression gain over the nv encoder (6 dB of PSNR) as well as a substantial improvement
Topologicallyaware overlay construction and server selection
, 2002
"... A number of largescale distributed Internet applications could potentially benefit from some level of knowledge about the relative proximity between its participating host nodes. For example, the performance of large overlay networks could be improved if the applicationlevel connectivity between ..."
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Cited by 341 (3 self)
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knowledge of a small number of wellknown landmark nodes) and completely distributed (requiring no communication or cooperation between the nodes being binned). We apply this binning strategy to the two applications mentioned above: overlay network construction and server selection. We test our binning
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