Introduction to parallel algorithms and architectures: array, trees, hypercubes
Introduction to parallel algorithms and architectures: array, trees, hypercubes
A still better performance guarantee for approximate graph coloring
Information Processing Letters
Computational Complexity
On the hardness of approximating optimum schedule problems in store and forward networks
IEEE/ACM Transactions on Networking (TON)
Some optimal inapproximability results
STOC '97 Proceedings of the twenty-ninth annual ACM symposium on Theory of computing
Approximate graph coloring by semidefinite programming
Journal of the ACM (JACM)
Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Approximating Satisfiable Satisfiability Problems (Extended Abstract)
ESA '97 Proceedings of the 5th Annual European Symposium on Algorithms
Zero Knowledge and the Chromatic Number
CCC '96 Proceedings of the 11th Annual IEEE Conference on Computational Complexity
Clique is hard to approximate within n1-
FOCS '96 Proceedings of the 37th Annual Symposium on Foundations of Computer Science
A QPTAS for TSP with fat weakly disjoint neighborhoods in doubling metrics
SODA '10 Proceedings of the twenty-first annual ACM-SIAM symposium on Discrete Algorithms
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In this paper we prove explicit lower bounds on the approximability of some graph problems restricted to instances which are already colored with a constant number of colors. As far as we know, this is the first time these problems are explicitily defined and analyzed. This allows us to drastically improve the previously known inapproximability results which were mainly a consequence of the analysis of bounded-degree graph problems. Moreover, we apply one of these results to obtain new lower bounds on the approximabiluty of the minimum delay schedule problem on store-and-forward networks of bounded diameter. Finally, we propose a generalization of our analysis of the complexity of approximating colored-graph problems to the complexity of approximating approximated optimization problems.