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Results 1 - 10
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7,436
Improved Boosting Algorithms Using Confidence-rated Predictions
- MACHINE LEARNING
, 1999
"... We describe several improvements to Freund and Schapire’s AdaBoost boosting algorithm, particularly in a setting in which hypotheses may assign confidences to each of their predictions. We give a simplified analysis of AdaBoost in this setting, and we show how this analysis can be used to find impr ..."
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Cited by 940 (26 self)
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improved parameter settings as well as a refined criterion for training weak hypotheses. We give a specific method for assigning confidences to the predictions of decision trees, a method closely related to one used by Quinlan. This method also suggests a technique for growing decision trees which turns
The Cyclical Behavior of Equilibrium Unemployment and Vacancies
- American Economic Review
, 2005
"... This paper argues that a broad class of search models cannot generate the observed business-cycle-frequency fluctuations in unemployment and job vacancies in response to shocks of a plausible magnitude. In the U.S., the vacancy-unemployment ratio is 20 times as volatile as average labor productivity ..."
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Cited by 871 (23 self)
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productivity, while under weak assumptions, search models predict that the vacancy-unemployment ratio and labor productivity have nearly the same variance. I establish this claim both using analytical comparative statics in a very general deterministic search model and using simulations of a stochastic version
Sparse coding with an overcomplete basis set: a strategy employed by V1
- Vision Research
, 1997
"... The spatial receptive fields of simple cells in mammalian striate cortex have been reasonably well described physiologically and can be characterized as being localized, oriented, and ban@ass, comparable with the basis functions of wavelet transforms. Previously, we have shown that these receptive f ..."
Abstract
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Cited by 958 (9 self)
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for representing a given input, and so the input-output function will deviate from being purely linear. These deviations from linearity provide a potential explanation for the weak forms of non-linearity observed in the response properties of cortical simple cells, and they further make predictions about
Investing for the long run when returns are predictable
- Journal of Finance
, 2000
"... We examine how the evidence of predictability in asset returns affects optimal portfolio choice for investors with long horizons. Particular attention is paid to estimation risk, or uncertainty about the true values of model parameters. We find that even after incorporating parameter uncertainty, th ..."
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Cited by 444 (0 self)
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, there is enough predictability in returns to make investors allocate substantially more to stocks, the longer their horizon. Moreover, the weak statistical significance of the evidence for predictability makes it important to take estimation risk into account; a long-horizon investor who ignores it may
Machine Learning: Structured prediction, weakly-supervised learning
"... Contact Information Research ..."
Randomized Experiments from Non-random Selection in the U.S. House Elections
- Journal of Econometrics
, 2008
"... This paper establishes the relatively weak conditions under which causal inferences from a regression-discontinuity (RD) analysis can be as credible as those from a randomized experiment, and hence under which the validity of the RD design can be tested by examining whether or not there is a discont ..."
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Cited by 377 (17 self)
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This paper establishes the relatively weak conditions under which causal inferences from a regression-discontinuity (RD) analysis can be as credible as those from a randomized experiment, and hence under which the validity of the RD design can be tested by examining whether or not there is a
A Critique of Software Defect Prediction Models
- IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
, 1999
"... Many organizations want to predict the number of defects (faults) in software systems, before they are deployed, to gauge the likely delivered quality and maintenance effort. To help in this numerous software metrics and statistical models have been developed, with a correspondingly large literatur ..."
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Cited by 292 (21 self)
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Many organizations want to predict the number of defects (faults) in software systems, before they are deployed, to gauge the likely delivered quality and maintenance effort. To help in this numerous software metrics and statistical models have been developed, with a correspondingly large
A Bayesian networks approach for predicting protein-protein interactions from genomic data
- SCIENCE
, 2003
"... We developed an approach using Bayesian networks to predict protein-protein interactions genome-wide in yeast. Our method naturally weights and combines into reliable predictions genomic features only weakly associated with interaction (e.g., mRNA co-expression, co-essentiality and co-localization). ..."
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Cited by 294 (11 self)
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We developed an approach using Bayesian networks to predict protein-protein interactions genome-wide in yeast. Our method naturally weights and combines into reliable predictions genomic features only weakly associated with interaction (e.g., mRNA co-expression, co-essentiality and co
A New Model to Predict Weak Lensing Peak Counts I. Comparison with N-body Simulations
, 2014
"... Context. Weak-lensing peak counts has been shown to be a powerful tool for cosmology. It provides non-Gaussian information of large scale structures, complementary to second order statistics. Aims. We propose a new flexible method to predict weak lensing peak counts, which can be adapted to realisti ..."
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Context. Weak-lensing peak counts has been shown to be a powerful tool for cosmology. It provides non-Gaussian information of large scale structures, complementary to second order statistics. Aims. We propose a new flexible method to predict weak lensing peak counts, which can be adapted
Toward an epistemology of physics
- Cognition and Instruction, 12(2 – 3), 105
, 1993
"... The aim of this work is twofold: to understand the intuitive sense of mechanism that accounts for commonsense predictions, expectations, explanations, and judg-ments of plausibility concerning mechanically causal situations and to understand how those intuitive ideas contribute to and develop into s ..."
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Cited by 285 (4 self)
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The aim of this work is twofold: to understand the intuitive sense of mechanism that accounts for commonsense predictions, expectations, explanations, and judg-ments of plausibility concerning mechanically causal situations and to understand how those intuitive ideas contribute to and develop
Results 1 - 10
of
7,436
