[PDF] Top 20 Model selection for simplicial approximation
Has 10000 "Model selection for simplicial approximation" found on our website. Below are the top 20 most common "Model selection for simplicial approximation".
Model selection for simplicial approximation
... a simplicial complex is seen as a model selection problem in the context of density ...our model selection ...Each simplicial complex C is associated to a set S C of possible ... Voir le document complet
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POD-based model order reduction with an adaptive snapshot selection for a discontinuous Galerkin approximation of the time-domain Maxwell's equations
... POD for reducing the complexity of the full time-domain simulation and running with the same basis for different ...assimilation). For example, we can run the full DGTD simulation with a reference ... Voir le document complet
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Integral equation solutions as prior distributions for Bayesian model selection
... The resulting priors have been called integral priors and the main advan- tage of the class of integral priors over the class of intrinsic priors proposed in Berger and Pericchi (1996) is that provided the Markov chain ... Voir le document complet
13
Model selection for sparse high-dimensional learning
... motivation for ARD was mostly heuristic, similarly to the lasso, good theoretical properties were discovered later on ( Wipf and Nagarajan , 2008 ; Wipf et ...scores for the ...Bayesian model ... Voir le document complet
164
Selection of sparse multifractional model
... processes for the last fty ...a model for speculative prices, as we read in its posthumous autobiography ...admissible model for stock ...martingale model is just a good ... Voir le document complet
26
A probabilistic model for data cube compression and query approximation
... saturated model. The complexity of the model may be controlled by removing some parameters (or setting them to zero), which adds the corresponding degrees of ...the model deviates pro- gressively ... Voir le document complet
10
A Greedy Sparse Approximation Algorithm Based On L1-Norm Selection Rules
... atom selection stage of MP, OMP and OLS is a one-step procedure, which is a short-term vision of the selection ...algorithms. For illustration purposes, let us consider a sparse deconvolution ... Voir le document complet
6
Efficient semiparametric estimation and model selection for multidimensional mixtures
... We are in particular interested in constructing optimal procedures for the estimation of θ. Optimal may be understood as efficient, in Le Cam’s theory point of view which is about asymptotic distribution and ... Voir le document complet
38
MSE Approximation for Model-based Compression of Multiresolution Semiregular Meshes
... MSE approximation in a model-based bit allocation improves the coding performance of a wavelet coder for any kind of semiregular meshes and any version of the Butterfly-based lifting scheme: the ... Voir le document complet
5
A quadratic lower bound for colourful simplicial depth
... we are using vertices of colour 2 which were not used in the first step, the colourful simplices generated at this step are distinct from those generated at the first step. This yields d − 1 colourful simplices. Repeat ... Voir le document complet
4
On some simplicial elimination schemes for chordal graphs
... tool for the stru tural study of hordal graphs, namely the Redu ed Clique ...that for any hordal graph we an onstru t in linear time a simpli ial elimination s heme starting with a pending maximal lique ... Voir le document complet
9
CMIP5 model selection for ISMIP6 ice sheet model forcing: Greenland and Antarctica
... Global Model Analysis (RGMA) component of the Earth and Environ- mental System Modeling (EESM) program (HiLAT-RASM project) and the DOE Office of Science (Biological and Environmental Research), Early Career ... Voir le document complet
26
Modelling and numerical approximation for the nonconservative bitemperature Euler model
... This paper is organised as follows. The second section is dedicated to the physical models that are involved in this paper. Firstly Euler bitemperature macroscopic model is given and we consider the Vlasov-BGK ... Voir le document complet
34
An Efficient Representation for Filtrations of Simplicial Complexes
... algorithms for computing per- sistent homology of a filtration using the CSD ...Γi for specific complexes such as the Rips complex or the relaxed Delaunay complex by assuming some notion of geometric ... Voir le document complet
25
Mis-parametrization subsets for a penalized least squares model selection
... the true sub-model with probability tending to 1 as soon as the sequence of pe- nalization rates tends to infinity and verifies c n = o(d −1 n ).Condition (3.1) above is not very restrictive and is verified in ... Voir le document complet
10
A non asymptotic penalized criterion for Gaussian mixture model selection
... 2007, for an ...the model dimension, and an oracle inequality with explicit constants is ...tial model (Castellan, 2003). For situations when these sharp calculations are impossible to obtain, ... Voir le document complet
37
Criteria for longitudinal data model selection based on Kullback's symmetric divergence
... situations. For instance, Hurvich and Tsai [16] proposed a corrected AIC (AICc) for linear and non-linear regression and autoregressive ...(KICc) for linear ...KICc for multiple to ... Voir le document complet
15
Approximation-tolerant model-based compressive sensing
... tail approximation oracle T 0 iterates x i+1 ← T k 0 (x i + Φ T (y − Φx i )) , (16) which in the first iteration gives x 1 ← T k 0 (Φ T y) ...0 for i 6= 1, ...O(1))-RIP for small δ, IHT needs to ... Voir le document complet
27
Criteria for longitudinal data model selection based on Kullback’s symmetric divergence
... to model selection for longitudinal data with correlated ...two model selection criteria: the first one is obtained by applying the maximum likelihood approach and the second is RICc ... Voir le document complet
18
Model selection in supervised classification
... Key-words: Generative Classification, Integrated likelihood, Integrated conditional likelihood, Classification entropy, Cross validated error rate, AIC and BIC criteria.... Sélection de [r] ... Voir le document complet
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