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Orthogonal Matching Pursuit with Noisy and Missing Data: Low and High Dimensional Results
Orthogonal Matching Pursuit Noisy and Missing Data High Dimensional Results Statistics Theory
2012/6/21
Many models for sparse regression typically assume that the covariates are known completely, and without noise. Particularly in high-dimensional applications, this is often not the case. This paper de...
Laplace deconvolution with noisy observations
adaptivity kernel estimation minimax rates Volterra equation Laplace convolution
2011/9/6
Abstract: In the present paper we consider Laplace deconvolution on the basis of discrete noisy data observed on the interval which length may increase with a sample size. Although this problem arises...
On the Stability of Swarm Consensus Under Noisy Control
Adaptation and Self-Organizing Systems (nlin.AO) Multiagent Systems (cs.MA)
2010/11/10
Representation of a swarm of independent robotic agents under graph-theoretic constructs allows for more formal analysis of convergence properties. We consider the local and global convergence behavio...
Near-Oracle Performance of Greedy Block-Sparse Estimation Techniques from Noisy Measurements
Near-Oracle Performance Greedy Block-Sparse Estimation Techniques Noisy Measurements
2010/11/30
This paper examines the ability of greedy algorithms to estimate a block sparse parameter vector from noisy measurements.In particular, block sparse versions of the orthogonal
matching pursuit and th...
Uniqueness transition in noisy phase retrieval
Uniqueness transition noisy phase retrieval
2010/12/16
Previous criteria for the feasibility of reconstructing phase information from intensity measurements, both in x-ray crystallography and more recently in coherent x-ray imaging, have been based on the...