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Metric Selection in Fast Dual Forward Backward Splitting
Metric Selection Fast Dual Forward Backward Splitting
2015/7/9
The performance of fast forward-backward splitting, or equivalently fast proximal gradient methods, is susceptible to conditioning of the optimization problem data. This conditioning is related to a m...
Monotonicity and Restart in Fast Gradient Methods
Monotonicity Restart Fast Gradient Methods
2015/7/9
Fast gradient methods are known to be non-monotone algorithms, and oscillations typically occur around the solution. To avoid this behavior, we propose in this paper a fast gradient method with restar...
First order optimization methods often perform poorly on ill-conditioned optimization problems. However, by preconditioning the problem data and solving the preconditioned problem, the performance of ...
Fast inference in generalized linear models via expected log-likelihoods
Fast inference generalized linear models expected log-likelihoods
2013/6/14
Generalized linear models play an essential role in a wide variety of statistical applications. This paper discusses an approximation of the likelihood in these models that can greatly facilitate comp...
MCMC methods for Gaussian process models using fast approximations for the likelihood
MCMC methods for Gaussian process models using fast approximations for the likelihood
2013/6/14
Gaussian Process (GP) models are a powerful and flexible tool for non-parametric regression and classification. Computation for GP models is intensive, since computing the posterior density, $\pi$, fo...
MCMC methods for Gaussian process models using fast approximations for the likelihood
MCMC methods for Gaussian process models using fast approximations for the likelihood
2013/6/14
Gaussian Process (GP) models are a powerful and flexible tool for non-parametric regression and classification. Computation for GP models is intensive, since computing the posterior density, $\pi$, fo...
Fast dimension-reduced climate model calibration
Fast dimension-reduced climate model calibration
2013/4/27
What is the response of the climate system to anthropogenic forcings? This question is addressed typically using projections from climate models. The uncertainty surrounding current climate projection...
A Fast Iterative Bayesian Inference Algorithm for Sparse Channel Estimation
A Fast Iterative Bayesian Inference Algorithm Sparse Channel Estimation
2013/4/27
In this paper, we present a Bayesian channel estimation algorithm for multicarrier receivers based on pilot symbol observations. The inherent sparse nature of wireless multipath channels is exploited ...
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...
The AEP algorithm for the fast computation of the distribution of the sum of dependent random variables
convolution istribution functions
2011/7/5
We propose a new algorithm to compute numerically the distribution function of the sum of $d$ dependent, non-negative random variables with given joint distribution.
Fast, Linear Time Hierarchical Clustering using the Baire Metric
Fast Linear Time Hierarchical Clustering using Baire Metric
2011/7/5
The Baire metric induces an ultrametric on a dataset and is of linear computational complexity, contrasted with the standard quadratic time agglomerative hierarchical clustering algorithm.