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669,562
For Most Large Underdetermined Systems of Linear Equations the Minimal ℓ1norm Solution is also the Sparsest Solution
 Comm. Pure Appl. Math
, 2004
"... We consider linear equations y = Φα where y is a given vector in R n, Φ is a given n by m matrix with n < m ≤ An, and we wish to solve for α ∈ R m. We suppose that the columns of Φ are normalized to unit ℓ 2 norm 1 and we place uniform measure on such Φ. We prove the existence of ρ = ρ(A) so that ..."
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Cited by 560 (10 self)
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We consider linear equations y = Φα where y is a given vector in R n, Φ is a given n by m matrix with n < m ≤ An, and we wish to solve for α ∈ R m. We suppose that the columns of Φ are normalized to unit ℓ 2 norm 1 and we place uniform measure on such Φ. We prove the existence of ρ = ρ(A) so
A standardized set of 260 pictures: Norms for name agreement, image agreement, familiarity, and visual complexity
 JOURNAL OF EXPERIMENTAL PSYCHOLOGY: HUMAN LEARNING AND MEMORY
, 1980
"... In this article we present a standardized set of 260 pictures for use in experiments investigating differences and similarities in the processing of pictures and words. The pictures are blackandwhite line drawings executed according to a set of rules that provide consistency of pictorial represent ..."
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Cited by 615 (1 self)
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In this article we present a standardized set of 260 pictures for use in experiments investigating differences and similarities in the processing of pictures and words. The pictures are blackandwhite line drawings executed according to a set of rules that provide consistency of pictorial representation. The pictures have been standardized on four variables of central relevance to memory and cognitive processing: name agreement, image agreement, familiarity, and visual complexity. The intercorrelations among the four measures were low, suggesting that the) ' are indices of different attributes of the pictures. The concepts were selected to provide exemplars from several widely studied semantic categories. Sources of naming variance, and mean familiarity and complexity of the exemplars, differed significantly across the set of categories investigated. The potential significance of each of the normative variables to a number of semantic and episodic memory tasks is discussed.
Does Social Capital Have an Economic Payoff? A CrossCountry Investigation
 Quarterly Journal of Economics
, 1997
"... This paper presents evidence that “social capital ” matters for measurable economic performance, using indicators of trust and civic norms from the World Values Surveys for a sample of 29 market economies. Memberships in formal groups—Putnam’s measure of social capital—is not associated with trust o ..."
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Cited by 1335 (8 self)
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This paper presents evidence that “social capital ” matters for measurable economic performance, using indicators of trust and civic norms from the World Values Surveys for a sample of 29 market economies. Memberships in formal groups—Putnam’s measure of social capital—is not associated with trust
Labor Contracts as Partial Gift Exchange
 Quarterly Journal of Economics
, 1982
"... This paper explains involuntary unemployment in terms of the response of firms to workers ' group behavior. Workers ' effort depends upon the norms determining a fair day's work. In order to affect those norms, firms may pay more than the marketclearing wage. Industries that pay cons ..."
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Cited by 762 (1 self)
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This paper explains involuntary unemployment in terms of the response of firms to workers ' group behavior. Workers ' effort depends upon the norms determining a fair day's work. In order to affect those norms, firms may pay more than the marketclearing wage. Industries that pay
GMRES: A generalized minimal residual algorithm for solving nonsymmetric linear systems
 SIAM J. SCI. STAT. COMPUT
, 1986
"... We present an iterative method for solving linear systems, which has the property ofminimizing at every step the norm of the residual vector over a Krylov subspace. The algorithm is derived from the Arnoldi process for constructing an l2orthogonal basis of Krylov subspaces. It can be considered a ..."
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Cited by 2046 (40 self)
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We present an iterative method for solving linear systems, which has the property ofminimizing at every step the norm of the residual vector over a Krylov subspace. The algorithm is derived from the Arnoldi process for constructing an l2orthogonal basis of Krylov subspaces. It can be considered
Fairness and Retaliation: The Economics of Reciprocity
 JOURNAL OF ECONOMIC PERSPECTIVES
, 2000
"... This paper shows that reciprocity has powerful implications for many economic domains. It is an important determinant in the enforcement of contracts and social norms and enhances the possibilities of collective action greatly. Reciprocity may render the provision of explicit incentive inefficient b ..."
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Cited by 553 (12 self)
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This paper shows that reciprocity has powerful implications for many economic domains. It is an important determinant in the enforcement of contracts and social norms and enhances the possibilities of collective action greatly. Reciprocity may render the provision of explicit incentive inefficient
Free Riding on Gnutella
, 2000
"... this paper, Gnutella is no exception to this finding, and an experimental study of its user patterns shows indeed that free riding is the norm rather than the exception. If distributed systems such as Gnutella rely on voluntary cooperation, rampant free riding may eventually render them useless, as ..."
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Cited by 610 (2 self)
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this paper, Gnutella is no exception to this finding, and an experimental study of its user patterns shows indeed that free riding is the norm rather than the exception. If distributed systems such as Gnutella rely on voluntary cooperation, rampant free riding may eventually render them useless
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
Stochastic Perturbation Theory
, 1988
"... . In this paper classical matrix perturbation theory is approached from a probabilistic point of view. The perturbed quantity is approximated by a firstorder perturbation expansion, in which the perturbation is assumed to be random. This permits the computation of statistics estimating the variatio ..."
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Cited by 886 (35 self)
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the variation in the perturbed quantity. Up to the higherorder terms that are ignored in the expansion, these statistics tend to be more realistic than perturbation bounds obtained in terms of norms. The technique is applied to a number of problems in matrix perturbation theory, including least squares
LucasKanade 20 Years On: A Unifying Framework: Part 3
 International Journal of Computer Vision
, 2002
"... Since the LucasKanade algorithm was proposed in 1981 image alignment has become one of the most widely used techniques in computer vision. Applications range from optical flow, tracking, and layered motion, to mosaic construction, medical image registration, and face coding. Numerous algorithms hav ..."
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Cited by 698 (30 self)
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first consider linear appearance variation when the error function is the Euclidean L2 norm. We describe three different algorithms, the simultaneous, project out, and normalization inverse compositional algorithms, and empirically compare them. Afterwards we consider the combination of linear
Results 1  10
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669,562