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A constant factor approximation algorithm for a class of classification problems
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Source Annual ACM Symposium on Theory of Computing archive
Proceedings of the thirty-second annual ACM symposium on Theory of computing table of contents
Portland, Oregon, United States
Pages: 652 - 658  
Year of Publication: 2000
ISBN:1-58113-184-4
Authors
Anupam Gupta  Computer Science Division, UC Berkeley, Berkeley, CA
Éva Tardos  Department of Computer Science, Cornell University, Ithaca, NY
Sponsor
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 5,   Downloads (12 Months): 34,   Citation Count: 12
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REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Michel Marie Deza and Monique Laurent. Geometry of Cuts and Metrics. Springer Verlag, 1997.
 
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Thomas G. Dietterich. Machine learning research: Four current directions. AI Magazine, 18(4):97-136, 1997.
 
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Stuart Geman and Donald Geman. Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images. IEEE Transactions on Pattern Analysis and Machine Intelligence, 6:721-741, 1984.
 
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D. Greig, B.T. Porteous, and A. Seheult. Exact maximum a posteriori estimation for binary images. J. Royal Statistical Society B, 51(2):271-279, 1989.
 
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CITED BY  12

Collaborative Colleagues:
Anupam Gupta: colleagues
Éva Tardos: colleagues