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Volumn , Issue , 2014, Pages 500-510

Learning sparse polynomial functions

Author keywords

[No Author keywords available]

Indexed keywords

TECHNOLOGY TRANSFER;

EID: 84902097261     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1137/1.9781611973402.37     Document Type: Conference Paper
Times cited : (29)

References (31)
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    • Learning an intersection of a constant number of halfspaces under a uniform distribution
    • BK97
    • [BK97] Avrim Blum and Ravi Kannan. Learning an intersection of a constant number of halfspaces under a uniform distribution. Journal of Computer and System Sciences, 54(2):371-380, 1997.
    • (1997) Journal of Computer and System Sciences , vol.54 , Issue.2 , pp. 371-380
    • Blum, A.1    Kannan, R.2
  • 5
    • 24144453496 scopus 로고    scopus 로고
    • Noise-tolerant learning, the parity problem, and the statistical query model
    • BKW03
    • [BKW03] Avrim Blum, Adam Kalai, and Hal Wasserman. Noise-tolerant learning, the parity problem, and the statistical query model. J. ACM, 50(4):506-519, 2003.
    • (2003) J. ACM , vol.50 , Issue.4 , pp. 506-519
    • Blum, A.1    Kalai, A.2    Wasserman, H.3
  • 7
    • 31744440684 scopus 로고    scopus 로고
    • Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information
    • CRT06
    • [CRT06] E. Candes, J. Romberg, and T. Tao. Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information. IEEE Transactions on Information Theory, 52:489 - 509, 2006.
    • (2006) IEEE Transactions on Information Theory , vol.52 , pp. 489-509
    • Candes, E.1    Romberg, J.2    Tao, T.3
  • 8
    • 33947416035 scopus 로고    scopus 로고
    • Near optimal signal recovery from random projections: Universal encoding strategies
    • CT06
    • [CT06] E. Candes and T. Tao. Near optimal signal recovery from random projections: Universal encoding strategies. IEEE 'Transactions on Information Theory, 2006.
    • (2006) IEEE 'Transactions on Information Theory
    • Candes, E.1    Tao, T.2
  • 12
    • 84861624238 scopus 로고    scopus 로고
    • Approximate sparse recovery: Optimizing time and measurements
    • GLPS12
    • [GLPS12] Anna C. Gilbert, Yi Li, Ely Porat, and Martin J. Strauss. Approximate sparse recovery: Optimizing time and measurements. SIAM J. Comput., 41(2):436- 453, 2012.
    • (2012) SIAM J. Comput. , vol.41 , Issue.2 , pp. 436-453
    • Gilbert, A.C.1    Li, Y.2    Porat, E.3    Strauss, M.J.4
  • 15
    • 84872440079 scopus 로고    scopus 로고
    • An invariance principle for polytopes
    • [HKM12], Previously in STOC'IO
    • [HKM12] Prahladh Harsha, Adam Klivans, and Raghu Meka. An invariance principle for polytopes. J. ACM, 59(29), 2012. Previously in STOC'IO.
    • (2012) J. ACM , vol.59 , Issue.29
    • Harsha, P.1    Klivans, A.2    Meka, R.3
  • 17
    • 0032202014 scopus 로고    scopus 로고
    • Efficient noise-tolerant learning from statistical queries
    • [Kea98],Previously in STOC'93
    • [Kea98] Michael Kearns. Efficient noise-tolerant learning from statistical queries. J. ACM, 45(6):983-1006, 1998. Previously in STOC'93.
    • (1998) J. ACM , vol.45 , Issue.6 , pp. 983-1006
    • Kearns, M.1
  • 22
    • 0029403808 scopus 로고
    • On the sample complexity of pac learning halfspaces against the uniform distribution
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    • [Lon95] P. Long. On the sample complexity of pac learning halfspaces against the uniform distribution. IEEE Transactions on Neural Networks, 6(6): 1556- 1559, 1995.
    • (1995) IEEE Transactions on Neural Networks , vol.6 , Issue.6 , pp. 1556-1559
    • Long, P.1
  • 29
  • 30
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    • Finding correlations in sub- quadratic time, with applications to learning parities and juntas with noise
    • Val 12
    • [Val 12] Gregory Valiant. Finding correlations in sub- quadratic time, with applications to learning parities and juntas with noise. In Proceedings of the Symposium on Foundations of Computer Science (FOCS), 2012.
    • (2012) Proceedings of the Symposium on Foundations of Computer Science (FOCS)
    • Valiant, G.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.