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» Lower Bounds for Sparse Recovery
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ATMOS
2008
118views Optimization» more  ATMOS 2008»
13 years 8 months ago
Recoverable Robustness for Railway Rolling Stock Planning
Abstract. In this paper we explore the possibility of applying the notions of Recoverable Robustness and Price of Recoverability (introduced by [5]) to railway rolling stock planni...
Valentina Cacchiani, Alberto Caprara, Laura Galli,...
ICALP
1994
Springer
13 years 10 months ago
On the Cost of Recomputing: Tight Bounds on Pebbling with Faults
We introduce a formal framework to study the time and space complexity of computing with faulty memory. For the fault-free case, time and space complexities were studied using the...
Yonatan Aumann, Judit Bar-Ilan, Uriel Feige
CORR
2010
Springer
172views Education» more  CORR 2010»
13 years 6 months ago
The MUSIC Algorithm for Sparse Objects: A Compressed Sensing Analysis
The MUSIC algorithm, and its extension for imaging sparse extended objects, with noisy data is analyzed by compressed sensing (CS) techniques. A thresholding rule is developed to a...
Albert Fannjiang
INFOCOM
2011
IEEE
12 years 10 months ago
Approximate distance queries and compact routing in sparse graphs
—An approximate distance query data structure is a compact representation of a graph, and can be queried to approximate shortest paths between any pair of vertices. Any such data...
Rachit Agarwal, Philip Brighten Godfrey, Sariel Ha...
CORR
2010
Springer
207views Education» more  CORR 2010»
13 years 6 months ago
Collaborative Hierarchical Sparse Modeling
Sparse modeling is a powerful framework for data analysis and processing. Traditionally, encoding in this framework is performed by solving an 1-regularized linear regression prob...
Pablo Sprechmann, Ignacio Ramírez, Guillerm...