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Fast MCMC sampling for Markov jump processes and extensions
Markov jump process uniformization MCMC Gibbs sampler Markov-modulated Poisson process continuous-time Bayesian network
2012/9/17
Markov jump processes (or continuous-time Markov chains) are a simple and important class of continuous-time dynamical systems. In this paper, we tackle the problem of simu-lating from the posterior d...
Fast and Robust Recursive Algorithms for Separable Nonnegative Matrix Factorization
nonnegative matrix factorization algorithms separability robustness hyperspectral unmixing linear mixing model pure-pixel assumption
2012/9/17
In this paper, we study the nonnegative matrix factorization problem under the separability assumption (that is, there exists a cone spanned by a small subsetof the columns of the input nonnegative da...
Fast and Accurate Algorithms for Re-Weighted L1-Norm Minimization
Fast and Accurate Algorithms Re-Weighted L1-Norm Minimization
2012/9/17
To recover a sparse signal from an underdetermined system, we often solve a constrained`1-norm minimization problem. In many cases, the signal sparsity and the recovery performance can be further impr...
Fast Planar Correlation Clustering for Image Segmentation
Fast Planar Correlation Clustering Image Segmentation
2012/9/18
We describe a new optimization scheme for nding high-quality clusterings in planar graphs that uses weighted perfect matching as a subroutine. Our method provides lower-bounds on the energy of the op...
Fast nonparametric classification based on data depth
Alpha-procedure zonoid depth DD-plot pattern recog-nition supervised learning, misclassification rate
2012/9/19
A new procedure, calledDDα-procedure, is developed to solve the problem of classifyingd-dimensional objects into q≥2 classes. The pro-cedure is completely nonparametric; it usesq-dimensional depth plo...
Fast Inference of Interactions in Assemblies of Stochastic Integrate-and-Fire Neurons from Spike Recordings
Bayesian procedures noise variance activity of the salamander
2011/3/24
We present two Bayesian procedures to infer the interactions and external currents in an assembly of stochastic integrate-and-fire neurons from the recording of their spiking activity. The first proce...
Classification with minimax fast rates for classes of Bayes rules with sparse representation
Classification Sparsity Decision dyadic trees Minimax rates Aggregation
2009/9/16
We consider the classification problem on the cube $[0,1]^d$ when the Bayes rule is known to belong to some new functions classes. These classes are made of prediction rules satisfying some conditions...