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A NonLinear Variational Problem For Image Matching
 SIAM J. Sci. Comput
, 1994
"... Minimizing a nonlinear functional is presented as a way of obtaining a planar mapping which matches two similar images. A smoothing term is added to the nonlinear functional in order to penalize discontinuous and irregular solutions. One option for the smoothing term is a quadratic form generated ..."
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Cited by 71 (3 self)
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Minimizing a nonlinear functional is presented as a way of obtaining a planar mapping which matches two similar images. A smoothing term is added to the nonlinear functional in order to penalize discontinuous and irregular solutions. One option for the smoothing term is a quadratic form generated
NonLinear Variation of Gell Parameters with Composition in Alkali Feldspar Series
"... G eolo gy D e partment, S t anf ord U niuersity, S tanford, C alif ornia 94 3 0 5 For a given alkali feldspar series of constant degree of internal order (structural state) the unit cell parameters are strongly linear functions of composition. Residual variation about such regression lines exhibits ..."
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G eolo gy D e partment, S t anf ord U niuersity, S tanford, C alif ornia 94 3 0 5 For a given alkali feldspar series of constant degree of internal order (structural state) the unit cell parameters are strongly linear functions of composition. Residual variation about such regression lines exhibits
APosteriori Error Estimates for the Finite Element Solution of NonLinear Variational Problems
, 1997
"... For finite element methods (FEMs) aposteriori error estimates that base on the evaluation of the variational equation regarding higher order approximations are a very successful concept proposed by various authors. This thesis presents a very general framework for this kind of aposteriori error es ..."
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estimates for nonlinear variational problems on Banach spaces. The error estimates consider the errors arising from the FEM approximation, numerical integration and termination of the iterative solver. By balancing the discretization and termination error an optimal stopping criterion for the nonlinear
An introduction to variational methods for graphical models
 TO APPEAR: M. I. JORDAN, (ED.), LEARNING IN GRAPHICAL MODELS
"... ..."
Graphical models, exponential families, and variational inference
, 2008
"... The formalism of probabilistic graphical models provides a unifying framework for capturing complex dependencies among random variables, and building largescale multivariate statistical models. Graphical models have become a focus of research in many statistical, computational and mathematical fiel ..."
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Cited by 800 (26 self)
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likelihoods, marginal probabilities and most probable configurations. We describe how a wide varietyof algorithms — among them sumproduct, cluster variational methods, expectationpropagation, mean field methods, maxproduct and linear programming relaxation, as well as conic programming relaxations — can
Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation
, 2002
"... There are many sources of systematic variation in cDNA microarray experiments which affect the measured gene expression levels (e.g. differences in labeling efficiency between the two fluorescent dyes). The term normalization refers to the process of removing such variation. A constant adjustment is ..."
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Cited by 699 (9 self)
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There are many sources of systematic variation in cDNA microarray experiments which affect the measured gene expression levels (e.g. differences in labeling efficiency between the two fluorescent dyes). The term normalization refers to the process of removing such variation. A constant adjustment
Convex Analysis
, 1970
"... In this book we aim to present, in a unified framework, a broad spectrum of mathematical theory that has grown in connection with the study of problems of optimization, equilibrium, control, and stability of linear and nonlinear systems. The title Variational Analysis reflects this breadth. For a lo ..."
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Cited by 5350 (67 self)
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In this book we aim to present, in a unified framework, a broad spectrum of mathematical theory that has grown in connection with the study of problems of optimization, equilibrium, control, and stability of linear and nonlinear systems. The title Variational Analysis reflects this breadth. For a
A New Extension of the Kalman Filter to Nonlinear Systems
, 1997
"... The Kalman filter(KF) is one of the most widely used methods for tracking and estimation due to its simplicity, optimality, tractability and robustness. However, the application of the KF to nonlinear systems can be difficult. The most common approach is to use the Extended Kalman Filter (EKF) which ..."
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Cited by 747 (6 self)
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) which simply linearises all nonlinear models so that the traditional linear Kalman filter can be applied. Although the EKF (in its many forms) is a widely used filtering strategy, over thirty years of experience with it has led to a general consensus within the tracking and control community
Lambertian Reflectance and Linear Subspaces
, 2000
"... We prove that the set of all reflectance functions (the mapping from surface normals to intensities) produced by Lambertian objects under distant, isotropic lighting lies close to a 9D linear subspace. This implies that, in general, the set of images of a convex Lambertian object obtained under a wi ..."
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Cited by 514 (20 self)
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the effects of Lambertian materials as the analog of a convolution. These results allow us to construct algorithms for object recognition based on linear methods as well as algorithms that use convex optimization to enforce nonnegative lighting functions. Finally, we show a simple way to enforce non
Results 1  10
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1,157,743