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2,190
A TopDown Proof Procedure for Generalized Data Dependencies
"... . Data dependencies are well known in the context of relational database. They aim to specify constraints that the data must satisfy to model correctly the part of the world under consideration. The implication problem for dependencies is to decide whether a given dependency is logically implied by ..."
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Cited by 1 (1 self)
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directed. It also requires the dynamic creation of new symbols, which can turn out to be a costly operation. This paper introduces a new proof procedure which is topdown: from conclusion to hypothesis, that is goaldirected. The originality of this procedure is that it does not act as classical theorem proving
Pig Latin: A NotSoForeign Language for Data Processing
"... There is a growing need for adhoc analysis of extremely large data sets, especially at internet companies where innovation critically depends on being able to analyze terabytes of data collected every day. Parallel database products, e.g., Teradata, offer a solution, but are usually prohibitively e ..."
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Cited by 607 (13 self)
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There is a growing need for adhoc analysis of extremely large data sets, especially at internet companies where innovation critically depends on being able to analyze terabytes of data collected every day. Parallel database products, e.g., Teradata, offer a solution, but are usually prohibitively
Econometric methods for fractional response variables with an application to 401 (K) plan participation rates
, 1996
"... We develop attractive functional forms and simple quasilikelihood estimation methods for regression models with a fractional dependent variable. Compared with logodds type procedures, there is no difficulty in recovering the regression function for the fractional variable, and there is no need to ..."
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Cited by 472 (8 self)
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We develop attractive functional forms and simple quasilikelihood estimation methods for regression models with a fractional dependent variable. Compared with logodds type procedures, there is no difficulty in recovering the regression function for the fractional variable, and there is no need
Sparse signal reconstruction from limited data using FOCUSS: A reweighted minimum norm algorithm
 IEEE TRANS. SIGNAL PROCESSING
, 1997
"... We present a nonparametric algorithm for finding localized energy solutions from limited data. The problem we address is underdetermined, and no prior knowledge of the shape of the region on which the solution is nonzero is assumed. Termed the FOcal Underdetermined System Solver (FOCUSS), the algor ..."
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Cited by 368 (22 self)
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of the preceding iterative solutions. The algorithm is presented as a general estimation tool usable across different applications. A detailed analysis laying the theoretical foundation for the algorithm is given and includes proofs of global and local convergence and a derivation of the rate of convergence. A
Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure
, 2004
"... This paper presents a new approach to estimation and inference in panel data models with a multifactor error structure where the unobserved common factors are (possibly) correlated with exogenously given individualspecific regressors, and the factor loadings differ over the cross section units. The ..."
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Cited by 383 (44 self)
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This paper presents a new approach to estimation and inference in panel data models with a multifactor error structure where the unobserved common factors are (possibly) correlated with exogenously given individualspecific regressors, and the factor loadings differ over the cross section units
Stable Function Approximation in Dynamic Programming
 IN MACHINE LEARNING: PROCEEDINGS OF THE TWELFTH INTERNATIONAL CONFERENCE
, 1995
"... The success of reinforcement learning in practical problems depends on the ability tocombine function approximation with temporal difference methods such as value iteration. Experiments in this area have produced mixed results; there have been both notable successes and notable disappointments. Theo ..."
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Cited by 263 (6 self)
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. Theory has been scarce, mostly due to the difficulty of reasoning about function approximators that generalize beyond the observed data. We provide a proof of convergence for a wide class of temporal difference methods involving function approximators such as knearestneighbor, and show experimentally
Bayesian coalescent inference of past population dynamics from molecular sequences.
 Molecular Biology and Evolution,
, 2005
"... We introduce the Bayesian skyline plot, a new method for estimating past population dynamics through time from a sample of molecular sequences without dependence on a prespecified parametric model of demographic history. We describe a Markov chain Monte Carlo sampling procedure that efficiently sam ..."
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Cited by 203 (16 self)
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We introduce the Bayesian skyline plot, a new method for estimating past population dynamics through time from a sample of molecular sequences without dependence on a prespecified parametric model of demographic history. We describe a Markov chain Monte Carlo sampling procedure that efficiently
A multivariate technique for multiply imputing missing values using a sequence of regression models. Survey Methodology 27
, 2001
"... This article describes and evaluates a procedure for imputing missing values for a relatively complex data structure when the data are missing at random. The imputations are obtained by fitting a sequence of regression models and drawing values from the corresponding predictive distributions. The ty ..."
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Cited by 175 (8 self)
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This article describes and evaluates a procedure for imputing missing values for a relatively complex data structure when the data are missing at random. The imputations are obtained by fitting a sequence of regression models and drawing values from the corresponding predictive distributions
Coil sensitivity encoding for fast MRI. In:
 Proceedings of the ISMRM 6th Annual Meeting,
, 1998
"... New theoretical and practical concepts are presented for considerably enhancing the performance of magnetic resonance imaging (MRI) by means of arrays of multiple receiver coils. Sensitivity encoding (SENSE) is based on the fact that receiver sensitivity generally has an encoding effect complementa ..."
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Cited by 193 (3 self)
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complementary to Fourier preparation by linear field gradients. Thus, by using multiple receiver coils in parallel scan time in Fourier imaging can be considerably reduced. The problem of image reconstruction from sensitivity encoded data is formulated in a general fashion and solved for arbitrary coil
TopDown Vs. BottomUp Analyses Of Interlanguage Data: A Reply To Saito
"... this article. The GENMOD analysis parallels Young's (1991) VARBRUL analysis and the results reported in the appendix are comparable with the results reported in Young (1991), Table 15, pp. 144145. The only differences in the two analyses are: (a) In the GENMOD analysis we have included the spe ..."
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group, while in the original VARBRUL analysis only the significance of the factor group as a whole was tested. The GENMOD procedure analyzes the data set from Young (1991), namely a binomial distribution of the dependent variable consisting of 1,565 tokens. This distribution is modeled by 1
Results 1  10
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