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» Solving Sparse Linear Constraints
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CADE
2006
Springer
14 years 5 months ago
Solving Sparse Linear Constraints
Linear arithmetic decision procedures form an important part of theorem provers for program verification. In most verification benchmarks, the linear arithmetic constraints are dom...
Shuvendu K. Lahiri, Madanlal Musuvathi
CPC
2006
110views more  CPC 2006»
13 years 5 months ago
Solving Sparse Random Instances of Max Cut and Max 2-CSP in Linear Expected Time
Abstract. We show that a maximum cut of a random graph below the giantcomponent threshold can be found in linear space and linear expected time by a simple algorithm. In fact, the ...
Alexander D. Scott, Gregory B. Sorkin
ICIP
2010
IEEE
13 years 2 months ago
Gradient projection for linearly constrained convex optimization in sparse signal recovery
The 2- 1 compressed sensing minimization problem can be solved efficiently by gradient projection. In imaging applications, the signal of interest corresponds to nonnegative pixel...
Zachary T. Harmany, Daniel Thompson, Rebecca Wille...
ICASSP
2011
IEEE
12 years 8 months ago
Sparse video recovery using Linearly Constrained Gradient Projection
This paper concerns the reconstruction of a temporally-varying scene from a video sequence of noisy linear projections. Assuming that each video frame is sparse or compressible in...
Daniel Thompson, Zachary T. Harmany, Roummel F. Ma...
CORR
2004
Springer
152views Education» more  CORR 2004»
13 years 4 months ago
Non-negative matrix factorization with sparseness constraints
Non-negative matrix factorization (NMF) is a recently developed technique for finding parts-based, linear representations of non-negative data. Although it has successfully been a...
Patrik O. Hoyer