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Volumn 1, Issue , 2008, Pages 126-131

Strategyproof classification under constant hypotheses: A tale of two functions

Author keywords

[No Author keywords available]

Indexed keywords

BINARY LABELS; DATA POINTS; DECISION MAKERS; MACHINE LEARNING CLASSIFICATIONS; OPTIMAL DECISIONS; SELFISH AGENTS;

EID: 57749170449     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (10)

References (11)
  • 4
    • 0013411860 scopus 로고
    • Can PAC learning algorithms tolerate random attribute noise?
    • Goldman, S. A., and Sloan, R. H. 1995. Can PAC learning algorithms tolerate random attribute noise? Algorithmica 14(1):70-84.
    • (1995) Algorithmica , vol.14 , Issue.1 , pp. 70-84
    • Goldman, S.A.1    Sloan, R.H.2
  • 5
    • 4644369748 scopus 로고    scopus 로고
    • Nash Q-learning for general-sum stochastic games
    • Hu, J., and Wellman, M. 2004. Nash Q-learning for general-sum stochastic games. Journal of Machine Learning Research 4:1039-1069.
    • (2004) Journal of Machine Learning Research , vol.4 , pp. 1039-1069
    • Hu, J.1    Wellman, M.2
  • 6
    • 0027640858 scopus 로고
    • Learning in the presence of malicious errors
    • Kearns, M., and Li, M. 1993. Learning in the presence of malicious errors. SIAM J. on Computing 22(4):807-837.
    • (1993) SIAM J. on Computing , vol.22 , Issue.4 , pp. 807-837
    • Kearns, M.1    Li, M.2
  • 7
    • 0019213986 scopus 로고
    • Distributed interpretation: A model and experiment
    • Lesser, V. R., and Erman, L. D. 1980. Distributed interpretation: A model and experiment. IEEE Transactions on Computers 29(12): 1144-1163.
    • (1980) IEEE Transactions on Computers , vol.29 , Issue.12 , pp. 1144-1163
    • Lesser, V.R.1    Erman, L.D.2
  • 8
    • 0000511449 scopus 로고
    • Redundant noisy attributes, attribute errors, and linear-threshold learning using Winnow
    • Littlestone, N. 1991. Redundant noisy attributes, attribute errors, and linear-threshold learning using Winnow. In COLT, 147-156.
    • (1991) COLT , pp. 147-156
    • Littlestone, N.1
  • 9
    • 85149834820 scopus 로고
    • Markov games as a framework for multi-agent reinforcement learning
    • Littman, M. L. 1994. Markov games as a framework for multi-agent reinforcement learning. in ICML, 157-163.
    • (1994) ICML , pp. 157-163
    • Littman, M.L.1
  • 10
    • 84926076710 scopus 로고    scopus 로고
    • Introduction to mechanism design (for computer scientists)
    • Nisan, N, Roughgarden, T, Tar-dos, E, and Vazirani, V, eds, Cambridge University Press, chapter 9
    • Nisan, N. 2007. Introduction to mechanism design (for computer scientists). In Nisan, N.; Roughgarden, T.; Tar-dos, E.; and Vazirani, V., eds., Algorithmic Game Theory. Cambridge University Press, chapter 9.
    • (2007) Algorithmic Game Theory
    • Nisan, N.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.