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» Approximating max-min linear programs with local algorithms
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ICALP
2005
Springer
15 years 7 months ago
How Well Can Primal-Dual and Local-Ratio Algorithms Perform?
We define an algorithmic paradigm, the stack model, that captures many primal-dual and local-ratio algorithms for approximating covering and packing problems. The stack model is ...
Allan Borodin, David Cashman, Avner Magen
125
Voted
ICASSP
2010
IEEE
15 years 2 months ago
A convex relaxation for approximate maximum-likelihood 2D source localization from range measurements
This paper addresses the problem of locating a single source from noisy range measurements in wireless sensor networks. An approximate solution to the maximum likelihood location ...
Pinar Oguz-Ekim, João Pedro Gomes, Jo&atild...
IJCNN
2000
IEEE
15 years 6 months ago
Piecewise Linear Homeomorphisms: The Scalar Case
The class of piecewise linear homeomorphisms (PLH) provides a convenient functional representation for many applications wherein an approximation to data is required that is inver...
Richard E. Groff, Daniel E. Koditschek, Pramod P. ...
117
Voted
FOCS
2005
IEEE
15 years 7 months ago
Sampling-based Approximation Algorithms for Multi-stage Stochastic
Stochastic optimization problems provide a means to model uncertainty in the input data where the uncertainty is modeled by a probability distribution over the possible realizatio...
Chaitanya Swamy, David B. Shmoys
119
Voted
DAGSTUHL
2007
15 years 3 months ago
Sampling-based Approximation Algorithms for Multi-stage Stochastic Optimization
Stochastic optimization problems provide a means to model uncertainty in the input data where the uncertainty is modeled by a probability distribution over the possible realizatio...
Chaitanya Swamy, David B. Shmoys