Results 1 - 10
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19,152
Probabilistic Principal Component Analysis
- JOURNAL OF THE ROYAL STATISTICAL SOCIETY, SERIES B
, 1999
"... Principal component analysis (PCA) is a ubiquitous technique for data analysis and processing, but one which is not based upon a probability model. In this paper we demonstrate how the principal axes of a set of observed data vectors may be determined through maximum-likelihood estimation of paramet ..."
Abstract
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Cited by 709 (5 self)
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Principal component analysis (PCA) is a ubiquitous technique for data analysis and processing, but one which is not based upon a probability model. In this paper we demonstrate how the principal axes of a set of observed data vectors may be determined through maximum-likelihood estimation
Indivisible labor and the business cycle
- Journal of Monetary Economics
, 1985
"... A growth model with shocks to technology is studied. Labor is indivisible, so all variability in hours worked is due to fluctuations in the number employed. We find that, unlike previous equilibrium models of the business cycle, this economy displays large fluctuations in hours worked and relatively ..."
Abstract
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Cited by 805 (10 self)
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A growth model with shocks to technology is studied. Labor is indivisible, so all variability in hours worked is due to fluctuations in the number employed. We find that, unlike previous equilibrium models of the business cycle, this economy displays large fluctuations in hours worked
Mixtures of Probabilistic Principal Component Analysers
, 1998
"... Principal component analysis (PCA) is one of the most popular techniques for processing, compressing and visualising data, although its effectiveness is limited by its global linearity. While nonlinear variants of PCA have been proposed, an alternative paradigm is to capture data complexity by a com ..."
Abstract
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Cited by 532 (6 self)
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maximum-likelihood framework, based on a specific form of Gaussian latent variable model. This leads to a well-defined mixture model for probabilistic principal component analysers, whose parameters can be determined using an EM algorithm. We discuss the advantages of this model in the context
High dimensional graphs and variable selection with the Lasso
- ANNALS OF STATISTICS
, 2006
"... The pattern of zero entries in the inverse covariance matrix of a multivariate normal distribution corresponds to conditional independence restrictions between variables. Covariance selection aims at estimating those structural zeros from data. We show that neighborhood selection with the Lasso is a ..."
Abstract
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Cited by 736 (22 self)
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is a computationally attractive alternative to standard covariance selection for sparse high-dimensional graphs. Neighborhood selection estimates the conditional independence restrictions separately for each node in the graph and is hence equivalent to variable selection for Gaussian linear models. We
EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis
- J. Neurosci. Methods
"... Abstract: We have developed a toolbox and graphic user interface, EEGLAB, running under the cross-platform MATLAB environment (The Mathworks, Inc.) for processing collections of single-trial and/or averaged EEG data of any number of channels. Available functions include EEG data, channel and event i ..."
Abstract
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Cited by 886 (45 self)
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information importing, data visualization (scrolling, scalp map and dipole model plotting, plus multi-trial ERP-image plots), preprocessing (including artifact rejection, filtering, epoch selection, and averaging), Independent Component Analysis (ICA) and time/frequency decompositions including channel
An Overview of Workflow Management: From Process Modeling to Workflow Automation Infrastructure
- DISTRIBUTED AND PARALLEL DATABASES
, 1995
"... Today’s business enterprises must deal with global competition, reduce the cost of doing business, and rapidly develop new services and products. To address these requirements enterprises must constantly reconsider and optimize the way they do business and change their information systems and appl ..."
Abstract
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Cited by 670 (26 self)
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and applications to support evolving business processes. Workflow technology facilitates these by providing methodologies and software to support (i) business process modeling to capture business processes as workflow specifications, (ii) business process reengineering to optimize specified processes, and (iii
Modeling Strategic Relationships for Process Reengineering
, 1995
"... Existing models for describing a process (such as a business process or a software development process) tend to focus on the \what " or the \how " of the process. For example, a health insurance claim process would typically be described in terms of a number of steps for assessing and appr ..."
Abstract
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Cited by 550 (40 self)
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Existing models for describing a process (such as a business process or a software development process) tend to focus on the \what " or the \how " of the process. For example, a health insurance claim process would typically be described in terms of a number of steps for assessing
Proposed NIST Standard for Role-Based Access Control
, 2001
"... In this article we propose a standard for role-based access control (RBAC). Although RBAC models have received broad support as a generalized approach to access control, and are well recognized for their many advantages in performing large-scale authorization management, no single authoritative def ..."
Abstract
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Cited by 544 (13 self)
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on defining a fundamental and stable set of RBAC components. This standard is organized into the RBAC Reference Model and the RBAC System and Administrative Functional Specification. The reference model defines the scope of features that comprise the standard and provides a consistent vocabulary in support
Gradient-based learning applied to document recognition
- Proceedings of the IEEE
, 1998
"... Multilayer neural networks trained with the back-propagation algorithm constitute the best example of a successful gradientbased learning technique. Given an appropriate network architecture, gradient-based learning algorithms can be used to synthesize a complex decision surface that can classify hi ..."
Abstract
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Cited by 1533 (84 self)
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to deal with the variability of two dimensional (2-D) shapes, are shown to outperform all other techniques. Real-life document recognition systems are composed of multiple modules including field extraction, segmentation, recognition, and language modeling. A new learning paradigm, called graph
Mediation in experimental and nonexperimental studies: new procedures and recommendations
- PSYCHOLOGICAL METHODS
, 2002
"... Mediation is said to occur when a causal effect of some variable X on an outcome Y is explained by some intervening variable M. The authors recommend that with small to moderate samples, bootstrap methods (B. Efron & R. Tibshirani, 1993) be used to assess mediation. Bootstrap tests are powerful ..."
Abstract
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Cited by 696 (4 self)
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size is small or suppression is a possibility. Empirical examples and computer setups for bootstrap analyses are provided. Mediation models of psychological processes are popular because they allow interesting associations to be decomposed into components that reveal possible causal mechanisms
Results 1 - 10
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19,152