A still better performance guarantee for approximate graph coloring
Information Processing Letters
Free Bits, PCPs, and Nonapproximability---Towards Tight Results
SIAM Journal on Computing
Zero knowledge and the chromatic number
Journal of Computer and System Sciences - Eleventh annual conference on structure and complexity 1996
Approximation algorithms
The importance of being biased
STOC '02 Proceedings of the thiry-fourth annual ACM symposium on Theory of computing
Truth revelation in approximately efficient combinatorial auctions
Journal of the ACM (JACM)
On the Approximation Properties of Independent Set Problem in Degree 3 Graphs
WADS '95 Proceedings of the 4th International Workshop on Algorithms and Data Structures
On the Power of Priority Algorithms for Facility Location and Set Cover
APPROX '02 Proceedings of the 5th International Workshop on Approximation Algorithms for Combinatorial Optimization
Models of greedy algorithms for graph problems
SODA '04 Proceedings of the fifteenth annual ACM-SIAM symposium on Discrete algorithms
Priority algorithms for graph optimization problems
Theoretical Computer Science
Approximation algorithms for combinatorial problems
Journal of Computer and System Sciences
Priority algorithms for graph optimization problems
Theoretical Computer Science
Note: On exponential time lower bound of Knapsack under backtracking
Theoretical Computer Science
Randomized priority algorithms
Theoretical Computer Science
Further reflections on a theory for basic algorithms
AAIM'06 Proceedings of the Second international conference on Algorithmic Aspects in Information and Management
Priority algorithms for the subset-sum problem
COCOON'07 Proceedings of the 13th annual international conference on Computing and Combinatorics
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We continue the study of priority or “greedy-like” algorithms as initiated in [6] and as extended to graph theoretic problems in [9]. Graph theoretic problems pose some modelling problems that did not exist in the original applications of [6] and [2]. Following [9], we further clarify these concepts. In the graph theoretic setting there are several natural input formulations for a given problem and we show that priority algorithm bounds in general depend on the input formulation. We study a variety of graph problems in the context of arbitrary and restricted priority models corresponding to known “greedy algorithms”.