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IPCO
2004
144views Optimization» more  IPCO 2004»
13 years 9 months ago
Hedging Uncertainty: Approximation Algorithms for Stochastic Optimization Problems
Abstract. We study two-stage, finite-scenario stochastic versions of several combinatorial optimization problems, and provide nearly tight approximation algorithms for them. Our pr...
R. Ravi, Amitabh Sinha
IPL
2007
105views more  IPL 2007»
13 years 7 months ago
Approximability of identifying codes and locating-dominating codes
We study the approximability and inapproximability of finding identifying codes and locating-dominating codes of the minimum size. In general graphs, we show that it is possible ...
Jukka Suomela
ADCM
2000
45views more  ADCM 2000»
13 years 7 months ago
Training neural networks with noisy data as an ill-posed problem
This paper is devoted to the analysis of network approximation in the framework of approximation and regularization theory. It is shown that training neural networks and similar n...
Martin Burger, Heinz W. Engl
CSR
2009
Springer
13 years 8 months ago
Approximability of the Maximum Solution Problem for Certain Families of Algebras
We study the approximability of the maximum solution problem. This problem is an optimisation variant of the constraint satisfaction problem and it captures a wide range of interes...
Peter Jonsson, Johan Thapper
SIAMNUM
2010
120views more  SIAMNUM 2010»
13 years 2 months ago
Sparse Spectral Approximations of High-Dimensional Problems Based on Hyperbolic Cross
Hyperbolic cross approximations by some classical orthogonal polynomials/functions in both bounded and unbounded domains are considered in this paper. Optimal error estimates in pr...
Jie Shen, Li-lian Wang