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Results 1 - 10
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2,095,770
A New Empirical Study of Weak Backdoors
"... Abstract. Work by Kilby, Slaney, Thiebaux and Walsh [1] showed that the backdoors and backbones of unstructured Random 3SAT instances are largely disjoint. In this work we extend this study to the consideration of backdoors in SAT encodings of structured problems. We show that the results of Kilby e ..."
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Cited by 4 (0 self)
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Abstract. Work by Kilby, Slaney, Thiebaux and Walsh [1] showed that the backdoors and backbones of unstructured Random 3SAT instances are largely disjoint. In this work we extend this study to the consideration of backdoors in SAT encodings of structured problems. We show that the results of Kilby
The Strength of Weak Ties: A Network Theory Revisited
- Sociological Theory
, 1982
"... In this chapter I review empirical studies directly testing the ..."
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Cited by 851 (2 self)
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In this chapter I review empirical studies directly testing the
The strength of weak learnability
- Machine Learning
, 1990
"... Abstract. This paper addresses the problem of improving the accuracy of an hypothesis output by a learning algorithm in the distribution-free (PAC) learning model. A concept class is learnable (or strongly learnable) if, given access to a Source of examples of the unknown concept, the learner with h ..."
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Cited by 861 (24 self)
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notions of learnability are equivalent. A method is described for converting a weak learning algorithm into one that achieves arbitrarily high accuracy. This construction may have practical applications as a tool for efficiently converting a mediocre learning algorithm into one that performs extremely
Reopening the Convergence Debate: A new look at cross-country growth empirics
- JOURNAL OF ECONOMIC GROWTH
, 1996
"... ..."
Power-law distributions in empirical data
- ISSN 00361445. doi: 10.1137/ 070710111. URL http://dx.doi.org/10.1137/070710111
, 2009
"... Power-law distributions occur in many situations of scientific interest and have significant consequences for our understanding of natural and man-made phenomena. Unfortunately, the empirical detection and characterization of power laws is made difficult by the large fluctuations that occur in the t ..."
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Cited by 589 (7 self)
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Power-law distributions occur in many situations of scientific interest and have significant consequences for our understanding of natural and man-made phenomena. Unfortunately, the empirical detection and characterization of power laws is made difficult by the large fluctuations that occur
The empirical case for two systems of reasoning
, 1996
"... Distinctions have been proposed between systems of reasoning for centuries. This article distills properties shared by many of these distinctions and characterizes the resulting systems in light of recent findings and theoretical developments. One system is associative because its computations ref ..."
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Cited by 631 (4 self)
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and can simultaneously generate different solutions to a reasoning problem. The rule-based system can suppress the associative system but not completely inhibit it. The article reviews evidence in favor of the distinction and its characterization.
Risk, Return and Equilibrium: Empirical Tests
- Journal of Political Economy
, 1973
"... Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at ..."
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Cited by 1445 (10 self)
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Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at
Boosting a Weak Learning Algorithm By Majority
, 1995
"... We present an algorithm for improving the accuracy of algorithms for learning binary concepts. The improvement is achieved by combining a large number of hypotheses, each of which is generated by training the given learning algorithm on a different set of examples. Our algorithm is based on ideas pr ..."
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Cited by 516 (15 self)
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We present an algorithm for improving the accuracy of algorithms for learning binary concepts. The improvement is achieved by combining a large number of hypotheses, each of which is generated by training the given learning algorithm on a different set of examples. Our algorithm is based on ideas
Loopy Belief Propagation for Approximate Inference: An Empirical Study
- In Proceedings of Uncertainty in AI
, 1999
"... 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 performa ..."
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Cited by 680 (18 self)
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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
Determinants of Economic Growth: A Cross-Country Empirical Study
, 1996
"... Empirical findings for a panel of around 100 countries from 1960 to 1990 strongly support the general notion of conditional convergence. For a given starting level of real per capita GDP, the growth rate is enhanced by higher initial schooling and life expectancy, lower fertility, lower government c ..."
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Cited by 859 (14 self)
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Empirical findings for a panel of around 100 countries from 1960 to 1990 strongly support the general notion of conditional convergence. For a given starting level of real per capita GDP, the growth rate is enhanced by higher initial schooling and life expectancy, lower fertility, lower government
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