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40,563
Rendering of Surfaces from Volume Data
 IEEE COMPUTER GRAPHICS AND APPLICATIONS
, 1988
"... The application of volume rendering techniques to the display of surfaces from sampled scalar functions of three spatial dimensions is explored. Fitting of geometric primitives to the sampled data is not required. Images are formed by directly shading each sample and projecting it onto the picture ..."
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Cited by 875 (12 self)
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The application of volume rendering techniques to the display of surfaces from sampled scalar functions of three spatial dimensions is explored. Fitting of geometric primitives to the sampled data is not required. Images are formed by directly shading each sample and projecting it onto
Arrays – Data Step Efficiency
"... Arrays are a facility common to many programming languages, useful for programming efficiency. SAS ® data step arrays have a number of unique characteristics that make them especially useful in enhancing your coding productivity. This presentation will provide a useful tutorial on the rationale for ..."
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Arrays are a facility common to many programming languages, useful for programming efficiency. SAS ® data step arrays have a number of unique characteristics that make them especially useful in enhancing your coding productivity. This presentation will provide a useful tutorial on the rationale
Clustering by passing messages between data points
 Science
, 2007
"... Clustering data by identifying a subset of representative examples is important for processing sensory signals and detecting patterns in data. Such “exemplars ” can be found by randomly choosing an initial subset of data points and then iteratively refining it, but this works well only if that initi ..."
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Cited by 696 (8 self)
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so in less than onehundredth the amount of time. Clustering data based on a measure of similarity is a critical step in scientific data analysis and in engineering systems. A common approach is to use data to learn a set of centers such that the sum of
From Data Mining to Knowledge Discovery in Databases.
 AI Magazine,
, 1996
"... ■ Data mining and knowledge discovery in databases have been attracting a significant amount of research, industry, and media attention of late. What is all the excitement about? This article provides an overview of this emerging field, clarifying how data mining and knowledge discovery in database ..."
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Cited by 538 (0 self)
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brief summary of recent KDD realworld applications is provided. Definitions of KDD and data mining are provided, and the general multistep KDD process is outlined. This multistep process has the application of datamining algorithms as one particular step in the process. The datamining step
Calibrating noise to sensitivity in private data analysis
 In Proceedings of the 3rd Theory of Cryptography Conference
, 2006
"... Abstract. We continue a line of research initiated in [10, 11] on privacypreserving statistical databases. Consider a trusted server that holds a database of sensitive information. Given a query function f mapping databases to reals, the socalled true answer is the result of applying f to the datab ..."
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Cited by 649 (60 self)
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the ith row of the database and g maps database rows to [0, 1]. We extend the study to general functions f, proving that privacy can be preserved by calibrating the standard deviation of the noise according to the sensitivity of the function f. Roughly speaking, this is the amount that any single
Advanced DATA Step Topics
"... Understanding the intricacies of the DATA step can make all the difference in your SAS programs. Since arrays, SAS dates, and testing SAS programs will be addressed in other papers, this talk will focus on the use of more advanced techniques to capitalize on the power of the DATA step and working wi ..."
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Understanding the intricacies of the DATA step can make all the difference in your SAS programs. Since arrays, SAS dates, and testing SAS programs will be addressed in other papers, this talk will focus on the use of more advanced techniques to capitalize on the power of the DATA step and working
UserWritten DATA Step Functions
, 2007
"... For years, users have asked for the ability to write functions in DATA step syntax. The day has come when this is possible. In SAS ® 9, the FCMP procedure provides the ability to write functions using DATA step syntax. In SAS ® 9.2, these functions can be called from a DATA step. This paper explains ..."
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For years, users have asked for the ability to write functions in DATA step syntax. The day has come when this is possible. In SAS ® 9, the FCMP procedure provides the ability to write functions using DATA step syntax. In SAS ® 9.2, these functions can be called from a DATA step. This paper
A View Of The Em Algorithm That Justifies Incremental, Sparse, And Other Variants
 Learning in Graphical Models
, 1998
"... . The EM algorithm performs maximum likelihood estimation for data in which some variables are unobserved. We present a function that resembles negative free energy and show that the M step maximizes this function with respect to the model parameters and the E step maximizes it with respect to the d ..."
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Cited by 993 (18 self)
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. The EM algorithm performs maximum likelihood estimation for data in which some variables are unobserved. We present a function that resembles negative free energy and show that the M step maximizes this function with respect to the model parameters and the E step maximizes it with respect
Dynamic Conditional Correlation: A simple class of multivariate Generalized Autoregressive Conditional Heteroskedasticity Models.
 Journal of Business & Economic Statistics
, 2002
"... Abstract Time varying correlations are often estimated with Multivariate Garch models that are linear in squares and cross products of the data. A new class of multivariate models called dynamic conditional correlation (DCC) models is proposed. These have the flexibility of univariate GARCH models ..."
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Cited by 711 (17 self)
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Abstract Time varying correlations are often estimated with Multivariate Garch models that are linear in squares and cross products of the data. A new class of multivariate models called dynamic conditional correlation (DCC) models is proposed. These have the flexibility of univariate GARCH models
Generic Schema Matching with Cupid
 In The VLDB Journal
, 2001
"... Schema matching is a critical step in many applications, such as XML message mapping, data warehouse loading, and schema integration. In this paper, we investigate algorithms for generic schema matching, outside of any particular data model or application. We first present a taxonomy for past s ..."
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Cited by 604 (17 self)
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Schema matching is a critical step in many applications, such as XML message mapping, data warehouse loading, and schema integration. In this paper, we investigate algorithms for generic schema matching, outside of any particular data model or application. We first present a taxonomy for past
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