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SODA
2012
ACM
268views Algorithms» more  SODA 2012»
11 years 9 months ago
Analyzing graph structure via linear measurements
We initiate the study of graph sketching, i.e., algorithms that use a limited number of linear measurements of a graph to determine the properties of the graph. While a graph on n...
Kook Jin Ahn, Sudipto Guha, Andrew McGregor
CORR
2012
Springer
225views Education» more  CORR 2012»
12 years 2 months ago
Compressive Principal Component Pursuit
We consider the problem of recovering a target matrix that is a superposition of low-rank and sparse components, from a small set of linear measurements. This problem arises in co...
John Wright, Arvind Ganesh, Kerui Min, Yi Ma
CORR
2012
Springer
201views Education» more  CORR 2012»
12 years 2 months ago
Signal Recovery on Incoherent Manifolds
Suppose that we observe noisy linear measurements of an unknown signal that can be modeled as the sum of two component signals, each of which arises from a nonlinear sub-manifold ...
Chinmay Hegde, Richard G. Baraniuk
ICCV
2011
IEEE
12 years 6 months ago
Imaging via Three-dimensional Compressive Sampling
Compressive sampling (CS) aims at acquiring a signal at a sampling rate that is significantly below the Nyquist rate. Its main idea is that a signal can be decoded from incomplet...
Xianbiao Shu, Narendra Ahuja
ICASSP
2011
IEEE
12 years 10 months ago
Dense disparity estimation from linear measurements
This paper proposes a methodology to estimate the correlation model between a pair of images that are given under the form of linear measurements. We consider an image pair whose ...
Vijayaraghavan Thirumalai, Pascal Frossard
CIMAGING
2008
142views Hardware» more  CIMAGING 2008»
13 years 8 months ago
Greedy signal recovery and uncertainty principles
This paper seeks to bridge the two major algorithmic approaches to sparse signal recovery from an incomplete set of linear measurements
Deanna Needell, Roman Vershynin