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Changes in the Demand for Skilled Labor within U.S. Manufacturing Industries: Evidence from the Annual Survey of Manufacturing

by John Bound, Zvi Griliches - JOURNAL OF ECONOMICS , 1994
"... This paper investigates the shift in demand away from unskilled and toward skilled labor in U. S. manufacturing over the 1980s. Production labor-saving technological change is the chief explanation for this shift. That conclusion is based on three facts: (1) the shift is due mostly to increased use ..."
Abstract - Cited by 580 (6 self) - Add to MetaCart
This paper investigates the shift in demand away from unskilled and toward skilled labor in U. S. manufacturing over the 1980s. Production labor-saving technological change is the chief explanation for this shift. That conclusion is based on three facts: (1) the shift is due mostly to increased use

A Bayesian Framework for the Analysis of Microarray Expression Data: Regularized t-Test and Statistical Inferences of Gene Changes

by Pierre Baldi, Anthony D. Long - Bioinformatics , 2001
"... Motivation: DNA microarrays are now capable of providing genome-wide patterns of gene expression across many different conditions. The first level of analysis of these patterns requires determining whether observed differences in expression are significant or not. Current methods are unsatisfactory ..."
Abstract - Cited by 491 (6 self) - Add to MetaCart
language R. and Department of Biological Chemistry, College of Medicine, University of California, Irvine. To whom all correspondence should be addressed. Contact: pfbaldi@ics.uci.edu, tdlong@uci.edu. 1

Fuzzy extractors: How to generate strong keys from biometrics and other noisy data

by Yevgeniy Dodis, Rafail Ostrovsky, Leonid Reyzin, Adam Smith , 2008
"... We provide formal definitions and efficient secure techniques for • turning noisy information into keys usable for any cryptographic application, and, in particular, • reliably and securely authenticating biometric data. Our techniques apply not just to biometric information, but to any keying mater ..."
Abstract - Cited by 535 (38 self) - Add to MetaCart
if the input changes, as long as it remains reasonably close to the original. Thus, R can be used as a key in a cryptographic application. A secure sketch produces public information about its input w that does not reveal w, and yet allows exact recovery of w given another value that is close to w. Thus

Mediation in experimental and nonexperimental studies: new procedures and recommendations

by Patrick E. Shrout, Niall Bolger - PSYCHOLOGICAL METHODS , 2002
"... Mediation is said to occur when a causal effect of some variable X on an outcome Y is explained by some intervening variable M. The authors recommend that with small to moderate samples, bootstrap methods (B. Efron & R. Tibshirani, 1993) be used to assess mediation. Bootstrap tests are powerful ..."
Abstract - Cited by 696 (4 self) - Add to MetaCart
Mediation is said to occur when a causal effect of some variable X on an outcome Y is explained by some intervening variable M. The authors recommend that with small to moderate samples, bootstrap methods (B. Efron & R. Tibshirani, 1993) be used to assess mediation. Bootstrap tests are powerful

Loopy belief propagation for approximate inference: An empirical study. In:

by Kevin P Murphy , Yair Weiss , Michael I Jordan - 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 error-correcting codes. The most dramatic instance of this is the near Shannon-limit performanc ..."
Abstract - Cited by 676 (15 self) - Add to MetaCart
X passes to its parent U; is given by: and the message X sends to its child Y j is given by: k;Cj For noisy-or links between parents and children, there exists an analytic expression for 1r( x) and Ax ( u;) that avoids the exhaustive enumeration over parent config urations We made a slight

The Determinants of Credit Spread Changes.

by Pierre Collin-Dufresne , Robert S Goldstein , J Spencer Martin , Gurdip Bakshi , Greg Bauer , Dave Brown , Francesca Carrieri , Peter Christoffersen , Susan Christoffersen , Greg Duffee , Darrell Duffie , Vihang Errunza , Gifford Fong , Mike Gallmeyer , Laurent Gauthier , Rick Green , John Griffin , Jean Helwege , Kris Jacobs , Chris Jones , Andrew Karolyi , Dilip Madan , David Mauer , Erwan Morellec , Federico Nardari , N R Prabhala , Tony Sanders , Sergei Sarkissian , Bill Schwert , Ken Singleton , Chester Spatt , René Stulz - 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 ..."
Abstract - Cited by 422 (2 self) - Add to MetaCart
treasuries. As a consequence, their portfolios become extremely sensitive to changes in credit spreads rather than changes in bond yields. The distinction between changes in credit spreads and changes in corporate yields is significant: while an adjusted R 2 of 60 percent is obtained when regressing high

Time series tests of endogenous growth models

by Charles I. Jones - Quarterly Journal of Economics , 1995
"... According to endogenous growth theory, permanent changes in certain policy variables have permanent effects on the rate of economic growth. Empirically, however, U. S. growth rates exhibit no large persistent changes. Therefore, the determinants of long-run growth highlighted by a specific growth mo ..."
Abstract - Cited by 440 (0 self) - Add to MetaCart
model must similarly exhibit no large persistent changes, or the persistent movement in these variables must be offsetting. Otherwise, the growth model is inconsistent with time series evidence. This paper argues that many AK-style models and R&D-based models of endogenous growth are rejected

Policy gradient methods for reinforcement learning with function approximation.

by Richard S Sutton , David Mcallester , Satinder Singh , Yishay Mansour - In NIPS, , 1999
"... Abstract Function approximation is essential to reinforcement learning, but the standard approach of approximating a value function and determining a policy from it has so far proven theoretically intractable. In this paper we explore an alternative approach in which the policy is explicitly repres ..."
Abstract - Cited by 439 (20 self) - Add to MetaCart
proportional to the gradient: where α is a positive-definite step size. If the above can be achieved, then θ can usually be assured to converge to a locally optimal policy in the performance measure ρ. Unlike the value-function approach, here small changes in θ can cause only small changes in the policy

Indexing the Positions of Continuously Moving Objects

by Simonas Saltenis, Christian S. Jensen, Scott T. Leutenegger, Mario A. Lopez , 2000
"... The coming years will witness dramatic advances in wireless communications as well as positioning technologies. As a result, tracking the changing positions of objects capable of continuous movement is becoming increasingly feasible and necessary. The present paper proposes a novel, R # -tree base ..."
Abstract - Cited by 389 (20 self) - Add to MetaCart
The coming years will witness dramatic advances in wireless communications as well as positioning technologies. As a result, tracking the changing positions of objects capable of continuous movement is becoming increasingly feasible and necessary. The present paper proposes a novel, R # -tree

The Power of Convex Relaxation: Near-Optimal Matrix Completion

by Emmanuel J. Candès, Terence Tao , 2009
"... This paper is concerned with the problem of recovering an unknown matrix from a small fraction of its entries. This is known as the matrix completion problem, and comes up in a great number of applications, including the famous Netflix Prize and other similar questions in collaborative filtering. In ..."
Abstract - Cited by 359 (7 self) - Add to MetaCart
. In general, accurate recovery of a matrix from a small number of entries is impossible; but the knowledge that the unknown matrix has low rank radically changes this premise, making the search for solutions meaningful. This paper presents optimality results quantifying the minimum number of entries needed
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