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Volumn , Issue , 2008, Pages 383-392

Learning arithmetic circuits

Author keywords

[No Author keywords available]

Indexed keywords

ACCURATE PREDICTION; APPROXIMATE INFERENCE; ARITHMETIC CIRCUIT; CONDITIONAL DISTRIBUTION; GRAPHICAL MODEL; LEARNING MODELS; REAL WORLD DOMAIN; SCORE FUNCTION; TREE-WIDTH;

EID: 80053265590     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (76)

References (20)
  • 4
    • 85161968853 scopus 로고    scopus 로고
    • Efficient principled learning of thin junction trees
    • Chechetka, A., & Guestrin, C. (2008). Efficient principled learning of thin junction trees. In NIPS 20.
    • (2008) NIPS , vol.20
    • Chechetka, A.1    Guestrin, C.2
  • 5
    • 0002248815 scopus 로고    scopus 로고
    • A Bayesian approach to learning Bayesian networks with local structure
    • Chickering, D., Heckerman, D., & Meek, C. (1997). A Bayesian approach to learning Bayesian networks with local structure. Proc. UAI-97 (pp. 80-89).
    • (1997) Proc. UAI-97 , pp. 80-89
    • Chickering, D.1    Heckerman, D.2    Meek, C.3
  • 6
    • 0041919126 scopus 로고    scopus 로고
    • (Tech. Rept. MSR-TR-2002-103). Microsoft, Redmond, WA
    • Chickering, D. M. (2002). The WinMine toolkit (Tech. Rept. MSR-TR-2002-103). Microsoft, Redmond, WA.
    • (2002) The WinMine Toolkit
    • Chickering, D.M.1
  • 7
    • 2442696729 scopus 로고    scopus 로고
    • A logical approach to factoring belief networks
    • Darwiche, A. (2002). A logical approach to factoring belief networks. Proc. KR-02 (pp. 409-420).
    • (2002) Proc. KR-02 , pp. 409-420
    • Darwiche, A.1
  • 8
    • 1642413218 scopus 로고    scopus 로고
    • A differential approach to inference in bayesian networks
    • Darwiche, A. (2003). A differential approach to inference in Bayesian networks. J. ACM, 50, 280-305.
    • (2003) J. ACM , vol.50 , pp. 280-305
    • Darwiche, A.1
  • 9
    • 0000319411 scopus 로고    scopus 로고
    • Learning Bayesian networks with local structure
    • Friedman, N., & Goldszmidt, M. (1996). Learning Bayesian networks with local structure. Proc. UAI-96 (pp. 252-262).
    • (1996) Proc. UAI-96 , pp. 252-262
    • Friedman, N.1    Goldszmidt, M.2
  • 12
    • 0242540431 scopus 로고    scopus 로고
    • Mining complex models from arbitrarily large databases in constant time
    • Hulten, G., & Domingos, P. (2002). Mining complex models from arbitrarily large databases in constant time. Proc. KDD-02 (pp. 525-531).
    • (2002) Proc. KDD-02 , pp. 525-531
    • Hulten, G.1    Domingos, P.2
  • 16
    • 68949085535 scopus 로고    scopus 로고
    • (Tech. Rept.). Dept. CSE, Univ. Washington, Seattle, WA
    • Lowd, D., & Domingos, P. (2008). Learning arithmetic circuits (Tech. Rept.). Dept. CSE, Univ. Washington, Seattle, WA. http://www.cs.washington.edu/ homes/'lowd/-lactr.pdf
    • (2008) Learning Arithmetic Circuits
    • Lowd, D.1    Domingos, P.2
  • 19
    • 0030120958 scopus 로고    scopus 로고
    • On the hardness of approximate reasoning
    • Roth, D. (1996). On the hardness of approximate reasoning. Artif. Intel., 82, 273-302. (Pubitemid 126374156)
    • (1996) Artificial Intelligence , vol.82 , Issue.1-2 , pp. 273-302
    • Roth, D.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.