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15th edition of the European Conference on the Mathematics of Oil Recovery
mathematical science geosciences
2016/7/20
From 29 August to 1 September, the capital of the Netherlands with its famous canal-ridden inner city (UNESCO world heritage), will host he 15th edition of the European Conference on the Mathematics o...
15th European Conference on the Mathematics of Oil Recovery (ECMOR XV)
geosciences Oil Recovery
2016/7/20
From 29 August to 1 September, the capital of the Netherlands with its famous canal-ridden inner city (UNESCO world heritage), will host the 15th edition of the European Conference on the Mathematics ...
Multiscale Chirplets and Near-Optimal Recovery of Chirps
Minimax Estimation Chirps Recursive Partitioning Time-Frequency Analysis Local Cosines Adaptive Estimation Oracle Inequalities
2015/6/17
This paper considers the model problem of recovering a signal f(t) from noisy sampled measurements. The objects we wish to recover are chirps which are neither smoothly varying nor stationary but rath...
Stable Signal Recovery from Incomplete and Inaccurate Measurements
`1-minimization basis pursuit restricted orthonormality sparsity singular values of random matrices
2015/6/17
Suppose we wish to recover a vector x0 ∈ Rm (e.g. a digital signal or image) from incomplete and contaminated observations y = Ax0 + e; A is a n by m matrix with far fewer rows than columns (n m) an...
Tight Oracle Bounds for Low-rank Matrix Recovery from a Minimal Number of Random Measurements
Matrix completion The Dantzig selector oracle inequalities norm of random matrices convex optimization and semidefinite programming
2015/6/17
This paper presents several novel theoretical results regarding the recovery of a low-rank matrix from just a few measurements consisting of linear combinations of the matrix entries. We show that pro...
Optimal Recovery of Holomorphic Functions from Inaccurate Information about Radial Integration
Approximation Optimal Recovery Holomorphic
2013/1/30
This paper addresses the optimal recovery of functions from Hilbert spaces of functions on the unit disc. The estimation, or recovery, is performed from inaccurate information given by integration alo...
An Improved Kriging Interpolation Technique Based on SVM and Its Recovery Experiment in Oceanic Missing Data
Least Square Support Vector Machine Kriging Interpolation Variogram SVM-Kriging
2013/1/30
In Kriging interpolation, the types of variogram model are very finite, which make the variogram very difficult to describe the spatial distributional characteristics of true data. In order to overcom...
lp-Recovery of the Most Significant Subspace among Multiple Subspaces with Outliers
Best approximating subspace lp minimization as relaxation for l0 minimization
2011/3/3
We assume data sampled from a mixture of d-dimensional linear subspaces with outliers distributed symmetrically around the origin. We study the recovery of the global l0 subspace (i.e., with largest n...
This paper investigates universal polar coding schemes. In particular, a notion of ordering (called convolutional path) is introduced between probability distributions to determine when a polar compre...
A posteriori error estimator based on gradient recovery by averaging for convection-diffusion-reaction problems approximated by discontinuous Galerkin methods
averaging convection-diffusion-reaction problems discontinuous Galerkin methods
2010/11/9
We consider some (anisotropic and piecewise constant) convection-diffusion-reaction problems in domains of R2, approximated by a discontinuous Galerkin method with polynomials of any degree. We propos...
Analyzing Weighted $\ell_1$ Minimization for Sparse Recovery with Nonuniform Sparse Models\footnote{The results of this paper were presented in part at the International Symposium on Information Theory, ISIT 2009}
Analyzing Weighted $\ell_1$ Minimization Sparse Recovery International Symposium Information Theory
2010/12/8
In this paper we introduce a nonuniform sparsity model and analyze the performance of an optimized weighted ℓ1 minimization over that sparsity model. In particular, we focus on a model where the...
The Augmented Lagrange Multiplier Method for Exact Recovery of Corrupted Low-Rank Matrices
Low-rank matrix recovery or completion Robust principal component analysis Nuclear norm minimization
2010/12/13
This paper proposes scalable and fast algorithms for solving the Robust PCA problem, namely recovering a low-rank matrix with an unknown fraction of its entries being arbitrarily corrupted. This probl...
Templates for Convex Cone Problems with Applications to Sparse Signal Recovery
Optimal rst-order methods Nesterov's accelerated descent algorithms
2010/12/3
This paper develops a general framework for solving a variety of convex cone problems that
frequently arise in signal processing, machine learning, statistics, and other elds. The approach works as ...
Extended Range Profiling in Stepped-Frequency Radar with Sparse Recovery
Extended Range Profiling Stepped-Frequency Radar Sparse Recovery
2010/12/13
The newly emerging theory of compressed sensing
(CS) enables restoring a sparse signal from inadequate number of linear projections. Based on compressed sensing theory, a new algorithm of high-resolu...
Sampling and Recovery of Multidimensional Bandlimited Functions via Frames
Sampling and Recovery Multidimensional Bandlimited Functions
2010/12/3
In this paper, we investigate frames for L2[−, ]d consisting of exponential functions in connection to oversampling and nonuniform sampling of bandlimited func-tions.