Ranking under uncertainty

Proceedings of the 23rd Conference on Uncertainty in Artificial Intelligence, UAI 2007

Volumn , Issue , 2007, Pages 466-473

  Zuk, Or ^a   Ein Dor, Liat ^a,b   Domany, Eytan ^a  

^a WEIZMANN INSTITUTE OF SCIENCE   (Israel)

^b INTEL CORPORATION   (Israel)

Author keywords

[No Author keywords available]

Indexed keywords

ANALYTICAL METHOD; ANALYTICAL RESULTS; GENE SELECTION; MICROARRAY EXPERIMENTS; NOISE LEVELS; NOISY MEASUREMENTS; OBJECT SELECTION; REAL WORLD SITUATIONS; RELIABILITY EVALUATION; SIMILARITY MEASURE;

ARTIFICIAL INTELLIGENCE; EXPERIMENTS; GENES;

RELIABILITY;

EID: 80053192918     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (27)

1. V. Conitzer and T. Sandholm. Common Voting Protocols as Maximum Likelihood Estimators. In Proc. 21st Conf. Un. Art. Int., 145-152, 2005.
2. N. Ailon, M. Charikar and A. Newman. Aggregating inconsistent information: ranking and clustering. In Proc. 37th ACM Symp. Th. Comp., 684-693, 2005. (Pubitemid 43098641)
3. R. Bekkerman, R. El-Yaniv, N. Tishby and Y. Winter. Distributional Word Clusters vs. Words for Text Categorization. J. Mach. Learn. Res. 3:1183-1208, 2003.
4. G. Forman. An extensive empirical study of feature selection metrics for text classification. J. Mach. Learn. Res. 3:1289-1306, 2003.
5. L.J. van't Veer et al. Gene expression profiling predicts clinical outcome of breast cancer. Nature, 415:530-536, 2002. (Pubitemid 34130608)
6. D.G. Beer et al. Gene-expression profiles predict survival of patients with lung adenocarcinoma. Nat. Med. 8:816-824, 2002.
7. N. Iizuka et al. Oligonucleotide microarray for prediction of early intrahepatic recurrence of hepatocellular carcinoma after curative resection. Lancet 361:923929, 2003.
8. A. Rosenwald et al. The use of molecular profiling to predict survival after chemotherapy for diffuse large-B-cell lymphoma. N Engl. J. Med. 346:1937-1947, 2002. (Pubitemid 34651353)
9. E.J. Yeoh et al. Classification, subtype discovery, and prediction of outcome in pediatric acute lymphoblastic leukemia by gene expression profiling. Cancer Cell. 1:133-143, 2002.
10. Y. Wang et al. Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer. Lancet 365:671-679, 2005. (Pubitemid 40260888)
11. H. Zhao et al. Gene Expression Profiling Predicts Survival in Conventional Renal Cell Carcinoma. PLoS Med. 3:e13, 2006.
12. M. Deza and T. Huang. Metrics on permutations, a survey. J. Comb., Inf. and Sys. Sci. 23:173-185, 1998.
13. J. Kececioglu and D. Sankoff. Exact and approximation algorithms for sorting by reversals, with application to genome rearrangement. Algorithmica 13:180-210, 1995.
14. M.G. Kendall, (1938) "A New Measure of Rank Correlation. Biometrika 30(1-2):81-93 1938.
15. R. Fagin, R. Kumar and D. Sivakumar. Comparing Top k Lists. SIAM J. Discrete Math. 17:134-160, 2003.
16. N. Ailon. Aggregation of Partial Rankings, p-Ratings and Top-m Lists. In Proc. ACM-SIAM Symp. Disc. Alg., 2007.
17. L.G. Valiant. A theory of the learnable. Comm. ACM. 27:1134-1142, 1984.
18. K. Huang. Statistical Mechanics, eds. Wiley, J. & Sons (New York), 1963.
19. N. Bleistein, and R.A. Handelsman. Asymptotic Expansions of Integrals, Dover Publications, New York, 1986.
20. M.J. van de Vijver et al. A gene-expression signature as a predictor of survival in breast cancer. N. Engl. J. Med. 347:1999-2009, 2002. (Pubitemid 35461656)
21. L. Ein-Dor, I. Kela, G. Getz, D. Givol and E. Domany. Outcome signature genes in breast cancer: is there a unique set? Bioinformatics 21:171-178, 2005. (Pubitemid 40202018)
22. S. Michiels, S. Koscielny and C. Hill. Prediction of cancer outcome with microarrays: a multiple random validation strategy. Lancet 365:488-492, 2005. (Pubitemid 40215731)
23. J.P.A. Ioannidis. Microarrays and molecular research: noise discovery? Lancet 365:454-455, 2005. (Pubitemid 40215715)
24. R.A. Fisher. Frequency distribution of the values of the correlation coefficient in samples from an indefinitely large population. Biometrika 10:507-521, 1915.
25. R.A. Fisher. On the "probable error" of a coefficient of correlation deduced from a small sample. Metron 1:3-32, 1921.
26. C. Dwork, S.R. Kumar, M. Naor and D. Sivakumar. Rank Aggregation Methods for the Web. In Proc. 10th Int. World Wide Web Conf., 613-622, 2001.
27. L. Ein-Dor, O. Zuk and E. Domany. Thousands of samples are needed to generate a robust gene list for predicting outcome in cancer. Proc. Nat. Ac. Sci. 103:5923-5928, 2006.