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ModelBased Analysis of Oligonucleotide Arrays: Model Validation, Design Issues and Standard Error Application
, 2001
"... Background: A modelbased analysis of oligonucleotide expression arrays we developed previously uses a probesensitivity index to capture the response characteristic of a specific probe pair and calculates modelbased expression indexes (MBEI). MBEI has standard error attached to it as a measure of ..."
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Cited by 775 (28 self)
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reduces the variability of low expression estimates, and provides a natural method of calculating expression values for PMonly arrays. The standard errors attached to expression values can be used to assess the reliability of downstream analysis. Published: X Month 2001 Genome Biology...
Loopy belief propagation for approximate inference: An empirical study. In:
 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 errorcorrecting codes. The most dramatic instance of this is the near Shannonlimit performanc ..."
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Cited by 676 (15 self)
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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 errorcorrecting codes. The most dramatic instance of this is the near Shannon
Continuous representations of timeseries gene expression data
 J COMPUT BIOL
, 2003
"... We present algorithms for timeseries gene expression analysis that permit the principled estimation of unobserved time points, clustering, and dataset alignment. Each expression profile is modeled as a cubic spline (piecewise polynomial) that is estimated from the observed data and every time point ..."
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Cited by 96 (11 self)
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encountered by discrete approaches. In particular, our method allows for control of the number of degrees of freedom of the warp through the specification of parameterized functions, which helps to avoid overfitting. We demonstrate that our algorithm produces stable lowerror alignments on real expression
Practical logarithmic rasterization for lowerror shadow maps
"... Logarithmic shadow maps can deliver the same quality as competing shadow map algorithms with substantially less storage and bandwidth. We show how current GPU architectures can be modified incrementally to support rendering of logarithmic shadow maps at current GPU fill rates. Specifically, we modif ..."
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modify the rasterizer to support rendering to a nonuniform grid with the same watertight rasterization properties as current rasterizers. We also describe a depth compression scheme to handle the nonlinear primitives produced by logarithmic rasterization. Our proposed architecture enhancements align
Stable Flocking of Mobile Agents, Part I: Fixed Topology
 In IEEE Conference on decision and control
, 2003
"... This is the first of a twopart paper that investigates the stability properties of a system of multiple mobile agents with double integrator dynamics. In this first part we generate stable flocking motion for the group using a coordination control scheme which gives rise to smooth control laws for ..."
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Cited by 169 (10 self)
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This is the first of a twopart paper that investigates the stability properties of a system of multiple mobile agents with double integrator dynamics. In this first part we generate stable flocking motion for the group using a coordination control scheme which gives rise to smooth control laws
RASL: Robust Alignment by Sparse and Lowrank Decomposition for Linearly Correlated Images
, 2010
"... This paper studies the problem of simultaneously aligning a batch of linearly correlated images despite gross corruption (such as occlusion). Our method seeks an optimal set of image domain transformations such that the matrix of transformed images can be decomposed as the sum of a sparse matrix of ..."
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Cited by 161 (6 self)
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of errors and a lowrank matrix of recovered aligned images. We reduce this extremely challenging optimization problem to a sequence of convex programs that minimize the sum of ℓ1norm and nuclear norm of the two component matrices, which can be efficiently solved by scalable convex optimization techniques
Reduced basis approximation and a posteriori error estimation for affinely parametrized elliptic coercive partial differential equations
, 2008
"... ... reduced basis approximation and a posteriori error estimation for linear functional outputs of affinely parametrized elliptic coercive partial differential equations. The essential ingredients are (primaldual) Galerkin projection onto a lowdimensional space associated with a smooth “parametric ..."
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Cited by 204 (37 self)
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... reduced basis approximation and a posteriori error estimation for linear functional outputs of affinely parametrized elliptic coercive partial differential equations. The essential ingredients are (primaldual) Galerkin projection onto a lowdimensional space associated with a smooth
Stable Flocking of Mobile Agents, Part II: Dynamic Topology
 In IEEE Conference on Decision and Control
, 2003
"... This is the second of a twopart paper, investigating the stability properties of a system of multiple mobile agents with double integrator dynamics. In this second part, we allow the topology of the control interconnections between the agents in the group to vary with time. Specifically, the contro ..."
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Cited by 99 (4 self)
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/repulsive and alignment forces. The former ensure collision avoidance and cohesion of the group and the latter result to all agents attaining a common heading angle, exhibiting flocking motion. Despite the use of only local information and the time varying nature of agent interaction which affects the local controllers
Sampling from large matrices: an approach through geometric functional analysis
 Journal of the ACM
, 2006
"... Abstract. We study random submatrices of a large matrix A. We show how to approximately compute A from its random submatrix of the smallest possible size O(r log r) with a small error in the spectral norm, where r = �A�2 F /�A�22 is the numerical rank of A. The numerical rank is always bounded by, a ..."
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Cited by 132 (5 self)
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, and is a stable relaxation of, the rank of A. This yields an asymptotically optimal guarantee in an algorithm for computing lowrank approximations of A. We also prove asymptotically optimal estimates on the spectral norm and the cutnorm of random submatrices of A. The result for the cutnorm yields a
Geometrically Stable Sampling for the ICP Algorithm
 Proc. International Conference on 3D Digital Imaging and Modeling
, 2003
"... The Iterative Closest Point (ICP) algorithm is a widely used method for aligning threedimensional point sets. The quality of alignment obtained by this algorithm depends heavily on choosing good pairs of corresponding points in the two datasets. If too many points are chosen from featureless region ..."
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Cited by 65 (5 self)
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The Iterative Closest Point (ICP) algorithm is a widely used method for aligning threedimensional point sets. The quality of alignment obtained by this algorithm depends heavily on choosing good pairs of corresponding points in the two datasets. If too many points are chosen from featureless
Results 1  10
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