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» The Structure of Sparse Resultant Matrices
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ICCV
2009
IEEE
13 years 6 months ago
Learning with dynamic group sparsity
This paper investigates a new learning formulation called dynamic group sparsity. It is a natural extension of the standard sparsity concept in compressive sensing, and is motivat...
Junzhou Huang, Xiaolei Huang, Dimitris N. Metaxas
CORR
2010
Springer
149views Education» more  CORR 2010»
13 years 8 months ago
A probabilistic and RIPless theory of compressed sensing
This paper introduces a simple and very general theory of compressive sensing. In this theory, the sensing mechanism simply selects sensing vectors independently at random from a ...
Emmanuel J. Candès, Yaniv Plan
JACM
2011
152views more  JACM 2011»
12 years 11 months ago
Robust principal component analysis?
This paper is about a curious phenomenon. Suppose we have a data matrix, which is the superposition of a low-rank component and a sparse component. Can we recover each component i...
Emmanuel J. Candès, Xiaodong Li, Yi Ma, Joh...
CORR
2012
Springer
218views Education» more  CORR 2012»
12 years 4 months ago
Robust 1-bit compressed sensing and sparse logistic regression: A convex programming approach
This paper develops theoretical results regarding noisy 1-bit compressed sensing and sparse binomial regression. We demonstrate that a single convex program gives an accurate estim...
Yaniv Plan, Roman Vershynin
ASPDAC
2006
ACM
97views Hardware» more  ASPDAC 2006»
14 years 2 months ago
SASIMI: sparsity-aware simulation of interconnect-dominated circuits with non-linear devices
We present a technique for the fast and accurate simulation of largescale VLSI interconnects with nonlinear devices, called SASIMI. The numerical efficiency of this technique is ...
Jitesh Jain, Stephen Cauley, Cheng-Kok Koh, Venkat...