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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...
Efficient Point-to-Subspace Query in $\ell^1$ with Application to Robust Face Recognition
point-to-subspace distance nearest subspace search Cauchy projection ace recog-nition subspace modeling
2012/9/18
Motivated by vision tasks such as robust face and object recognition, we consider the follow-ing general problem: given a collection of low-dimensional linear subspaces in a high-dimensional ambient (...
A Robust, Fully Adaptive M-estimator for Pointwise Estimation in Heteroscedastic Regression
Adaptation Huber contrast Lepski’s method M-estimation minimax estimation nonparamet-ric regression pointwise estimation robust estimation.
2012/9/19
We introduce a robust and fully adaptive method for pointwise estimation in heteroscedastic regression. We allow for noise and design distributions that are unknown and fulfill very weak assumptions o...
Robust Bayesian inference of networks using Dirichlet t-distributions
Bayesian inference Dirichlet process graphical model Markov chain Monte Carlo t-distribution.
2012/9/18
Bayesian graphical modeling provides an appealing way to obtain uncertainty esti-mates when inferring network structures, and much recent progress has been made for Gaussian models. These models have ...
Robust Dequantized Compressive Sensing
compressive sensing signal reconstruction quantization optimization.
2012/9/18
We consider the reconstruction problem in compressed sensing in which the observations are recorded in a finite number of bits. They may thus contain quantization errors (from being rounded to the nea...
Relative Density-Ratio Estimation for Robust Distribution Comparison
Density ratio Pearson divergence Outlier detection
2011/7/6
Divergence estimators based on direct approximation of density-ratios without going through separate approximation of numerator and denominator densities have been successfully applied to machine lear...