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InvestmentCash Flow Sensitivities Are not Valid Measures of Financing Constraints
 Quarterly Journal of Economics
, 2000
"... Work by Kaplan and Zingales provides both theoretical arguments and empirical evidence that investmentcash �ow sensitivities are not good indicators of �nancing constraints. Fazzari, Hubbard, and Petersen {this Journal} criticize those �ndings. In this note we explain how the Fazzari et al. critici ..."
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Cited by 214 (0 self)
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on the differential sensitivity of corporate investment to cash �ow. Kaplan and Zingales {1997} (hereinafter, KZ) provide both theoretical arguments and empirical evidence that this differential sensitivity is not a valid measure of �nancing constraints. Fazzari, Hubbard, and Petersen {2000} (hereinafter, FHP {2000
The arguments of associations
"... This chapter considers associative solutions to “non‐linear ” discrimination problems, such as negative patterning (A+ and B+ vs AB‐) and the biconditional discrimination (AB+ and CD+ vs AC ‐ and BD‐). It is commonly assumed that the solution to these discriminations requires “configural ” elements ..."
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, as the arguments of associations, to have differential “presence ” on reinforced versus non‐ reinforced trials, and thus differential associability and control over responding. The chapter then presents a more specific version of one of these models, describing how interactions between stimuli, particularly
Scaling theorems for zero crossings
 IEEE Transactions on Pattern Analysis and Machine Intelligence
, 1986
"... We prove that the scale map of the zerocrossings of atmost all signals filtered by the second derivative of a gaussian of variable size determines the signal uniquely, up to a constant scaling and a harmonic function. Our proof provides a method for reconstructing almost all signals from knowledge ..."
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Cited by 181 (4 self)
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of how the zerocrossing contours of the signal, fitered by a gaussian filter, change with the size of the filter. The proof assumes that the filtered signal can be represented as a polynomial of finite, albeit possibly very high, order. An argument suggests that this restriction is not essential
SYSTEMS OF DIFFERENTIAL EQUATIONS WITH DEVIATING ARGUMENT
"... ABSTRACT. Sufficient conditions for existence of central integral manifolds are presented and iterative methods for building central integral manifolds suggested for linear systems of differential and integrodifferential equations with deviating arguments and quasilinear systems of differential eq ..."
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ABSTRACT. Sufficient conditions for existence of central integral manifolds are presented and iterative methods for building central integral manifolds suggested for linear systems of differential and integrodifferential equations with deviating arguments and quasilinear systems of differential
arguments: Sturmian comparison method in
, 2001
"... Differential equations with several deviating ..."
FUNCTIONALDIFFERENTIAL EQUATION WITH RETARDED ARGUMENT
"... Abstract. Sufficient conditions are obtained for all positive solutions of dx(t) dt = [f(x(t), x(t − τ))]x(t) to converges as t→ ∞ to a positive equilibrium solution. 1. ..."
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Abstract. Sufficient conditions are obtained for all positive solutions of dx(t) dt = [f(x(t), x(t − τ))]x(t) to converges as t→ ∞ to a positive equilibrium solution. 1.
with a deviated argument
, 2015
"... Periodic BVP for a class of nonlinear differential equation ..."
Decomposing hierarchical alignment: coarguments as conditions on alignment*
"... Apart from differential argument marking, referential hierarchies affect argument marking in two ways: (a) through hierarchical marking, where markers compete for a slot and the competition is resolved by a hierarchy, and (b) through coargument sensitivity, where the marking of one argument depends ..."
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Apart from differential argument marking, referential hierarchies affect argument marking in two ways: (a) through hierarchical marking, where markers compete for a slot and the competition is resolved by a hierarchy, and (b) through coargument sensitivity, where the marking of one argument
Differentially Private Feature Selection via Stability Arguments
 and the Robustness of the Lasso.” In Conference on Learning Theory
, 2013
"... We design differentially private algorithms for statistical model selection. Given a data set and a large, discrete collection of “models”, each of which is a family of probability distributions, the goal is to determine the model that best “fits ” the data. This is a basic problem in many areas of ..."
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Cited by 6 (1 self)
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We design differentially private algorithms for statistical model selection. Given a data set and a large, discrete collection of “models”, each of which is a family of probability distributions, the goal is to determine the model that best “fits ” the data. This is a basic problem in many areas
Results 11  20
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1,974