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constant Profile parameter, pressure angle
"... The profile gradient method has been recently introduced as a means of generating screw compressor rotor profiles. As a single parameter method, this procedure is convenient for the optimisation of screw compressor rotors and evaluating their quality. In this paper, the procedure is modified to adop ..."
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The profile gradient method has been recently introduced as a means of generating screw compressor rotor profiles. As a single parameter method, this procedure is convenient for the optimisation of screw compressor rotors and evaluating their quality. In this paper, the procedure is modified
An analysis of transformations
 Journal of the Royal Statistical Society. Series B (Methodological
, 1964
"... In the analysis of data it is often assumed that observations y,, y,,...,y, are independently normally distributed with constant variance and with expectations specified by a model linear in a set of parameters 0. In this paper we make the less restrictive assumption that such a normal, homoscedasti ..."
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Cited by 1067 (3 self)
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In the analysis of data it is often assumed that observations y,, y,,...,y, are independently normally distributed with constant variance and with expectations specified by a model linear in a set of parameters 0. In this paper we make the less restrictive assumption that such a normal
Bayesian Interpolation
 NEURAL COMPUTATION
, 1991
"... Although Bayesian analysis has been in use since Laplace, the Bayesian method of modelcomparison has only recently been developed in depth. In this paper, the Bayesian approach to regularisation and modelcomparison is demonstrated by studying the inference problem of interpolating noisy data. T ..."
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Cited by 728 (17 self)
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. `Occam's razor' is automatically embodied by this framework. The way in which Bayes infers the values of regularising constants and noise levels has an elegant interpretation in terms of the effective number of parameters determined by the data set. This framework is due to Gull and Skilling.
Face Recognition Based on Fitting a 3D Morphable Model
 IEEE TRANS. PATTERN ANAL. MACH. INTELL
, 2003
"... This paper presents a method for face recognition across variations in pose, ranging from frontal to profile views, and across a wide range of illuminations, including cast shadows and specular reflections. To account for these variations, the algorithm simulates the process of image formation in 3D ..."
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Cited by 551 (19 self)
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This paper presents a method for face recognition across variations in pose, ranging from frontal to profile views, and across a wide range of illuminations, including cast shadows and specular reflections. To account for these variations, the algorithm simulates the process of image formation in 3
Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
, 2001
"... Variable selection is fundamental to highdimensional statistical modeling, including nonparametric regression. Many approaches in use are stepwise selection procedures, which can be computationally expensive and ignore stochastic errors in the variable selection process. In this article, penalized ..."
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Cited by 948 (62 self)
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likelihood approaches are proposed to handle these kinds of problems. The proposed methods select variables and estimate coefficients simultaneously. Hence they enable us to construct confidence intervals for estimated parameters. The proposed approaches are distinguished from others in that the penalty
The Dantzig selector: statistical estimation when p is much larger than n
, 2005
"... In many important statistical applications, the number of variables or parameters p is much larger than the number of observations n. Suppose then that we have observations y = Ax + z, where x ∈ R p is a parameter vector of interest, A is a data matrix with possibly far fewer rows than columns, n ≪ ..."
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Cited by 879 (14 self)
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In many important statistical applications, the number of variables or parameters p is much larger than the number of observations n. Suppose then that we have observations y = Ax + z, where x ∈ R p is a parameter vector of interest, A is a data matrix with possibly far fewer rows than columns, n
ThreeYear Wilkinson Microwave Anisotropy Probe (WMAP) Observations: Implications for . . .
, 2007
"... A simple cosmological model with only six parameters (matter density, Ωmh 2, baryon density, Ωbh 2, Hubble Constant, H0, amplitude of fluctuations, σ8, optical ..."
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Cited by 379 (7 self)
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A simple cosmological model with only six parameters (matter density, Ωmh 2, baryon density, Ωbh 2, Hubble Constant, H0, amplitude of fluctuations, σ8, optical
Latent Semantic Models for Collaborative filtering
 ACM Trans. Information Systems
"... Collaborative filtering aims at learning predictive models of user preferences, interests or behavior from community data, that is, a database of available user preferences. In this article, we describe a new family of modelbased algorithms designed for this task. These algorithms rely on a statist ..."
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Cited by 331 (1 self)
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statistical modelling technique that introduces latent class variables in a mixture model setting to discover user communities and prototypical interest profiles. We investigate several variations to deal with discrete and continuous response variables as well as with different objective functions. The main
Timevarying NAIRU and its implications for Economic Policy
 NBER WORKING PAPER
, 1996
"... This paper estimates the NAIRU (standing for the nonaccelerating Inflation Rate of unemployment) as a parameter that varies over time. The NAIRU is the unemployment rate that is consistent with a constant rate of inflation. Its value is determined in an econometric model in which the inflation rate ..."
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Cited by 320 (4 self)
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This paper estimates the NAIRU (standing for the nonaccelerating Inflation Rate of unemployment) as a parameter that varies over time. The NAIRU is the unemployment rate that is consistent with a constant rate of inflation. Its value is determined in an econometric model in which the inflation
A control theoretic analysis of red,”
 in Proceedings of the 20th Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM ’01),
, 2001
"... AbstractIn this paper we use a previously developed nonlinear dynamic model of TCP to analyze and design Active Queue Management (AQM) control systems using RED. First, we linearize the interconnection of TCP and a bottlenecked queue and discuss its feedback properties in terms of network paramete ..."
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Cited by 290 (8 self)
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parameters such as link capacity, load and roundtrip time. Using this model, we next design an AQM control system using the random early detection (RED) scheme by relating its free parameters such as the lowpass filter break point and loss probability profile to the network parameters. We present
Results 1  10
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