Results 1 - 10 of 1,624

Attention, similarity, and the identification-Categorization Relationship

by Robert M. Nosofsky , 1986
"... A unified quantitative approach to modeling subjects ' identification and categorization of multidimensional perceptual stimuli is proposed and tested. Two subjects identified and categorized the same set of perceptually confusable stimuli varying on separable dimensions. The identification dat ..."
Abstract - Cited by 690 (28 self) - Add to MetaCart
A unified quantitative approach to modeling subjects ' identification and categorization of multidimensional perceptual stimuli is proposed and tested. Two subjects identified and categorized the same set of perceptually confusable stimuli varying on separable dimensions. The identification

Robust Inference with Multi-way Clustering

by A. Colin Cameron, Jonah B. Gelbach, Douglas L. Miller , 2006
"... In this paper we propose a new variance estimator for OLS as well as for nonlinear estimators such as logit, probit and GMM. This variance estimator enables cluster-robust inference when there is two-way or multi-way clustering that is nonnested. The variance estimator extends the standard cluster-r ..."
Abstract - Cited by 363 (4 self) - Add to MetaCart
In this paper we propose a new variance estimator for OLS as well as for nonlinear estimators such as logit, probit and GMM. This variance estimator enables cluster-robust inference when there is two-way or multi-way clustering that is nonnested. The variance estimator extends the standard cluster

Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure

by M. Hashem Pesaran , 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 individual-specific regressors, and the factor loadings differ over the cross section units. The ..."
Abstract - Cited by 383 (44 self) - Add to MetaCart
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 individual-specific regressors, and the factor loadings differ over the cross section units

Dimension Inference in Spreadsheets

by Chris Chambers, Martin Erwig
"... We present a reasoning system for inferring dimension information in spreadsheets. This system can be used to check the consistency of spreadsheet formulas and can be employed to detect errors in spreadsheets. We have prototypically implemented the system as an add-in to Excel. In an evaluation of t ..."
Abstract - Cited by 5 (4 self) - Add to MetaCart
We present a reasoning system for inferring dimension information in spreadsheets. This system can be used to check the consistency of spreadsheet formulas and can be employed to detect errors in spreadsheets. We have prototypically implemented the system as an add-in to Excel. In an evaluation

Dimension Inference under Polymorphic Recursion

by Mikael Rittri - In Proc. 7th Conf. Functional Programming Languages and Computer Architecture , 1995
"... Numeric types can be given polymorphic dimension parameters, in order to avoid dimension errors and unit errors. The most general dimensions can be inferred automatically. It has been observed that polymorphic recursion is more important for the dimensions than for the proper types. We show that, un ..."
Abstract - Cited by 13 (1 self) - Add to MetaCart
Numeric types can be given polymorphic dimension parameters, in order to avoid dimension errors and unit errors. The most general dimensions can be inferred automatically. It has been observed that polymorphic recursion is more important for the dimensions than for the proper types. We show that

On Cognition and Inference of Spatial Dimension in Korean

by Byong-rae Ryu
"... This paper examines the aspects of the infer-ences between the dimensional terms in Ko-rean, and tries to give an account of the in-ference patterns based on the interaction of gestalt and position properties of spatial ob-jects. Basically following Lang (1989), I ad-vance the idea that the inferenc ..."
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This paper examines the aspects of the infer-ences between the dimensional terms in Ko-rean, and tries to give an account of the in-ference patterns based on the interaction of gestalt and position properties of spatial ob-jects. Basically following Lang (1989), I ad-vance the idea

On k-anonymity and the curse of dimensionality

by Charu C. Aggarwal - In VLDB , 2005
"... In recent years, the wide availability of personal data has made the problem of privacy preserving data mining an important one. A number of methods have recently been proposed for privacy preserving data mining of multidimensional data records. One of the methods for privacy preserving data mining ..."
Abstract - Cited by 171 (4 self) - Add to MetaCart
of attributes which may be considered quasi-identifiers, it becomes difficult to anonymize the data without an unacceptably high amount of information loss. This is because an exponential number of combinations of dimensions can be used to make precise inference attacks, even when individual attributes

Dimension Types

by Andrew Kennedy - In 5th European Symp. on Programming, LNCS 788 , 1994
"... . Scientists and engineers must ensure that physical equations are dimensionally consistent, but existing programming languages treat all numeric values as dimensionless. This paper extends a strongly-typed programming language with a notion of dimension type. Our approach improves on previous propo ..."
Abstract - Cited by 33 (3 self) - Add to MetaCart
proposals in that dimension types may be polymorphic. Furthermore, any expression which is typable in the system has a most general type, and we describe an algorithm which infers this type automatically. The algorithm exploits equational unification over Abelian groups in addition to ordinary term

Automatic Dimension Inference and Checking for Object-Oriented Programs

by Sudheendra Hangal, Monica S. Lam
"... This paper introduces UniFi, a tool that attempts to automatically detect dimension errors in Java programs. UniFi infers dimensional relationships across primitive type and string variables in a program, using an inter-procedural, context-sensitive analysis. It then monitors these dimensional relat ..."
Abstract - Cited by 6 (0 self) - Add to MetaCart
This paper introduces UniFi, a tool that attempts to automatically detect dimension errors in Java programs. UniFi infers dimensional relationships across primitive type and string variables in a program, using an inter-procedural, context-sensitive analysis. It then monitors these dimensional

Ancillary Information For Statistical Inference

by D.A.S. Fraser, N. Reid , 1999
"... This paper focuses on the reduction from an initial data variable y of dimension N ..."
Abstract - Cited by 26 (14 self) - Add to MetaCart
This paper focuses on the reduction from an initial data variable y of dimension N
Results 1 - 10 of 1,624