Approximating discrete collections via local improvements
Proceedings of the sixth annual ACM-SIAM symposium on Discrete algorithms
TCS '00 Proceedings of the International Conference IFIP on Theoretical Computer Science, Exploring New Frontiers of Theoretical Informatics
Approximation Algorithms for MAX 4-SAT and Rounding Procedures for Semidefinite Programs
Proceedings of the 7th International IPCO Conference on Integer Programming and Combinatorial Optimization
Tight Bound on Johnson's Algoritihm for Max-SAT
CCC '97 Proceedings of the 12th Annual IEEE Conference on Computational Complexity
A Short Guide To Approximation Preserving Reductions
CCC '97 Proceedings of the 12th Annual IEEE Conference on Computational Complexity
MAX-2-SAT: how good is Tabu search in the worst-case?
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Approximation for minimum total dominating set
Proceedings of the 2nd International Conference on Interaction Sciences: Information Technology, Culture and Human
Complexity of determining the most vital elements for the 1-median and 1-center location problems
COCOA'10 Proceedings of the 4th international conference on Combinatorial optimization and applications - Volume Part I
A refined evaluation function for the MinLA problem
MICAI'06 Proceedings of the 5th Mexican international conference on Artificial Intelligence
A survey of approximation results for local search algorithms
Efficient Approximation and Online Algorithms
Max-Sum diversification, monotone submodular functions and dynamic updates
PODS '12 Proceedings of the 31st symposium on Principles of Database Systems
Complexity of determining the most vital elements for the p-median and p-center location problems
Journal of Combinatorial Optimization
Critical edges/nodes for the minimum spanning tree problem: complexity and approximation
Journal of Combinatorial Optimization
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We attempt to reconcile the two distinct views of approximation classes: syntactic and computational. Syntactic classes such as MAX SNP permit structural results and have natural complete problems, while computational classes such as APX allow us to work with classes of problems whose approximability is well-understood. Our results provide a syntactic characterization of computational classes, and give a computational framework for syntactic classes.