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» Approximation Algorithms for Clustering Problems
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155
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SARA
2007
Springer
16 years 17 days ago
Approximate Model-Based Diagnosis Using Greedy Stochastic Search
Most algorithms for computing diagnoses within a modelbased diagnosis framework are deterministic. Such algorithms guarantee soundness and completeness, but are NPhard. To overcom...
Alexander Feldman, Gregory M. Provan, Arjan J. C. ...
207
Voted
CVPR
2009
IEEE
17 years 1 months ago
Robust Multi-Class Transductive Learning with Graphs
Graph-based methods form a main category of semisupervised learning, offering flexibility and easy implementation in many applications. However, the performance of these methods...
Wei Liu (Columbia University), Shih-fu Chang (Colu...
ICASSP
2011
IEEE
14 years 10 months ago
Asymptotically MMSE-optimum pilot design for comb-type OFDM channel estimation in high-mobility scenarios
Under high mobility, the orthogonality between sub-carriers in an OFDM symbol is destroyed resulting in severe intercarrier interference (ICI). We present a novel algorithm to est...
K. M. Zahidul Islam, Tareq Y. Al-Naffouri, Naofal ...
GECCO
2008
Springer
148views Optimization» more  GECCO 2008»
15 years 7 months ago
Accelerating convergence using rough sets theory for multi-objective optimization problems
We propose the use of rough sets theory to improve the first approximation provided by a multi-objective evolutionary algorithm and retain the nondominated solutions using a new ...
Luis V. Santana-Quintero, Carlos A. Coello Coello
GECCO
2009
Springer
148views Optimization» more  GECCO 2009»
16 years 1 months ago
Multiplicative approximations and the hypervolume indicator
Indicator-based algorithms have become a very popular approach to solve multi-objective optimization problems. In this paper, we contribute to the theoretical understanding of alg...
Tobias Friedrich, Christian Horoba, Frank Neumann