Results 1 - 10 of 11,907

Mixtures of Probabilistic Principal Component Analysers

by Michael E. Tipping, Christopher M. Bishop , 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 - Cited by 532 (6 self) - Add to MetaCart
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

Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm

by Yongyue Zhang, Michael Brady, Stephen Smith - IEEE TRANSACTIONS ON MEDICAL. IMAGING , 2001
"... The finite mixture (FM) model is the most commonly used model for statistical segmentation of brain magnetic resonance (MR) images because of its simple mathematical form and the piecewise constant nature of ideal brain MR images. However, being a histogram-based model, the FM has an intrinsic limi ..."
Abstract - Cited by 639 (15 self) - Add to MetaCart
limitation—no spatial information is taken into account. This causes the FM model to work only on well-defined images with low levels of noise; unfortunately, this is often not the the case due to artifacts such as partial volume effect and bias field distortion. Under these conditions, FM model

Learnability in Optimality Theory

by Bruce Tesar, Paul Smolensky , 1995
"... In this article we show how Optimality Theory yields a highly general Constraint Demotion principle for grammar learning. The resulting learning procedure specifically exploits the grammatical structure of Optimality Theory, independent of the content of substantive constraints defining any given gr ..."
Abstract - Cited by 529 (35 self) - Add to MetaCart
efficient convergence to a correct grammar. We discuss implications for learning from overt data only, as well as other learning issues. We argue that Optimality Theory promotes confluence of the demands of more effective learnability and deeper linguistic explanation.

Qualitative process theory

by Kenneth D. Forbus - MIT AI Lab Memo , 1982
"... Objects move, collide, flow, bend, heat up, cool down, stretch, compress. and boil. These and other things that cause changes in objects over time are intuitively characterized as processes. To understand commonsense physical reasoning and make programs that interact with the physical world as well ..."
Abstract - Cited by 899 (92 self) - Add to MetaCart
as people do we must understand qualitative reasoning about processes, when they will occur, their effects, and when they will stop. Qualitative process theory defines a simple notion of physical process that appears useful as a language in which to write dynamical theories. Reasoning about processes also

Reconstruction and Representation of 3D Objects with Radial Basis Functions

by J. C. Carr, R. K. Beatson, J. B. Cherrie, T. J. Mitchell, W. R. Fright, B. C. McCallum, T. R. Evans - Computer Graphics (SIGGRAPH ’01 Conf. Proc.), pages 67–76. ACM SIGGRAPH , 2001
"... We use polyharmonic Radial Basis Functions (RBFs) to reconstruct smooth, manifold surfaces from point-cloud data and to repair incomplete meshes. An object's surface is defined implicitly as the zero set of an RBF fitted to the given surface data. Fast methods for fitting and evaluating RBFs al ..."
Abstract - Cited by 505 (1 self) - Add to MetaCart
We use polyharmonic Radial Basis Functions (RBFs) to reconstruct smooth, manifold surfaces from point-cloud data and to repair incomplete meshes. An object's surface is defined implicitly as the zero set of an RBF fitted to the given surface data. Fast methods for fitting and evaluating RBFs

Complexity-effective superscalar processors

by Subbarao Palacharla, J. E. Smith, et al. - IN PROCEEDINGS OF THE 24TH ANNUAL INTERNATIONAL SYMPOSIUM ON COMPUTER ARCHITECTURE , 1997
"... The performance tradeoff between hardware complexity and clock speed is studied. First, a generic superscalar pipeline is defined. Then the specific areas of register renaming, instruction window wakeup and selection logic, and operand bypassing are ana-lyzed. Each is modeled and Spice simulated for ..."
Abstract - Cited by 467 (5 self) - Add to MetaCart
The performance tradeoff between hardware complexity and clock speed is studied. First, a generic superscalar pipeline is defined. Then the specific areas of register renaming, instruction window wakeup and selection logic, and operand bypassing are ana-lyzed. Each is modeled and Spice simulated

Monopolistic competition and optimum product diversity. The American Economic Review,

by Avinash K Dixit , Joseph E Stiglitz , Harold Hotelling , Nicholas Stern , Kelvin Lancaster , Stiglitz , 1977
"... The basic issue concerning production in welfare economics is whether a market solution will yield the socially optimum kinds and quantities of commodities. It is well known that problems can arise for three broad reasons: distributive justice; external effects; and scale economies. This paper is c ..."
Abstract - Cited by 1911 (5 self) - Add to MetaCart
The basic issue concerning production in welfare economics is whether a market solution will yield the socially optimum kinds and quantities of commodities. It is well known that problems can arise for three broad reasons: distributive justice; external effects; and scale economies. This paper

Loopy belief propagation for approximate inference: An empirical study. In:

by Kevin P Murphy , Yair Weiss , Michael I Jordan - Proceedings of Uncertainty in AI, , 1999
"... Abstract Recently, researchers have demonstrated that "loopy belief propagation" -the use of Pearl's polytree algorithm in a Bayesian network with loops -can perform well in the context of error-correcting codes. The most dramatic instance of this is the near Shannon-limit performanc ..."
Abstract - Cited by 676 (15 self) - Add to MetaCart
Abstract Recently, researchers have demonstrated that "loopy belief propagation" -the use of Pearl's polytree algorithm in a Bayesian network with loops -can perform well in the context of error-correcting codes. The most dramatic instance of this is the near Shannon

Motivation through the Design of Work: Test of a Theory. Organizational Behavior and Human Performance,

by ] Richard Hackman , Grec R Oldham , 1976
"... A model is proposed that specifies the conditions under which individuals will become internally motivated to perform effectively on their jobs. The model focuses on the interaction among three classes of variables: (a) the psychological states of employees that must be present for internally motiv ..."
Abstract - Cited by 622 (2 self) - Add to MetaCart
A model is proposed that specifies the conditions under which individuals will become internally motivated to perform effectively on their jobs. The model focuses on the interaction among three classes of variables: (a) the psychological states of employees that must be present for internally

Practical animation of liquids

by Nick Foster, Dimitri Metaxas - Graphical Models and Image Processing , 1996
"... We present a comprehensive methodology for realistically animating liquid phenomena. Our approach unifies existing computer graphics techniques for simulating fluids and extends them by incorporating more complex behavior. It is based on the Navier-Stokes equations which couple momentum and mass con ..."
Abstract - Cited by 445 (26 self) - Add to MetaCart
models. Wave effects such as reflection, refraction and diffraction, as well as rotational effects such as eddies, vorticity, and splashing are a natural consequence of solving the system. In addition, the Lagrange equations of motion are used to place buoyant dynamic objects into a scene, and track
Results 1 - 10 of 11,907