메뉴 건너뛰기




Volumn , Issue , 2013, Pages 655-664

Statistical algorithms and a lower bound for detecting planted cliques

Author keywords

Lower bounds; Planted clique; Statistical algorithms; Statistical query

Indexed keywords

COMPUTATIONAL PROBLEM; CRYPTOGRAPHIC APPLICATIONS; LOWER BOUNDS; OPTIMAL LOWER BOUND; PLANTED CLIQUES; STATISTICAL ALGORITHM; STATISTICAL QUERIES; STATISTICAL QUERY MODELS;

EID: 84879828520     PISSN: 07378017     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2488608.2488692     Document Type: Conference Paper
Times cited : (103)

References (51)
  • 2
    • 0032284595 scopus 로고    scopus 로고
    • Finding a large hidden clique in a random graph
    • N. Alon, M. Krivelevich, and B. Sudakov. Finding a large hidden clique in a random graph. In SODA, pages 594-598, 1998.
    • (1998) SODA , pp. 594-598
    • Alon, N.1    Krivelevich, M.2    Sudakov, B.3
  • 3
    • 80052581489 scopus 로고    scopus 로고
    • Nuclear norm minimization for the planted clique and biclique problems
    • B. P. W. Ames and S. A. Vavasis. Nuclear norm minimization for the planted clique and biclique problems. Math. Program., 129(1):69-89, 2011.
    • (2011) Math. Program , vol.129 , Issue.1 , pp. 69-89
    • Ames, B.P.W.1    Vavasis, S.A.2
  • 4
    • 77954751550 scopus 로고    scopus 로고
    • Public-key cryptography from diffierent assumptions
    • B. Applebaum, B. Barak, and A. Wigderson. Public-key cryptography from diffierent assumptions. In STOC, pages 171-180, 2010.
    • (2010) STOC , pp. 171-180
    • Applebaum, B.1    Barak, B.2    Wigderson, A.3
  • 5
    • 84871752900 scopus 로고    scopus 로고
    • Computational complexity and information asymmetry in financial products (extended abstract)
    • S. Arora, B. Barak, M. Brunnermeier, and R. Ge. Computational complexity and information asymmetry in financial products (extended abstract). In ICS, pages 49-65, 2010.
    • (2010) ICS , pp. 49-65
    • Arora, S.1    Barak, B.2    Brunnermeier, M.3    Ge, R.4
  • 6
    • 70349271230 scopus 로고    scopus 로고
    • An efficient rescaled perceptron algorithm for conic systems
    • A. Belloni, R. M. Freund, and S. Vempala. An efficient rescaled perceptron algorithm for conic systems. Math. Oper. Res., 34(3):621-641, 2009.
    • (2009) Math. Oper. Res. , vol.34 , Issue.3 , pp. 621-641
    • Belloni, A.1    Freund, R.M.2    Vempala, S.3
  • 7
    • 77954702542 scopus 로고    scopus 로고
    • Detecting high log-densities: An o(n1/4) approximation for densest k-subgraph
    • A. Bhaskara, M. Charikar, E. Chlamtac, U. Feige, and A. Vijayaraghavan. Detecting high log-densities: an o(n1/4) approximation for densest k-subgraph. In STOC, pages 201-210, 2010.
    • (2010) STOC , pp. 201-210
    • Bhaskara, A.1    Charikar, M.2    Chlamtac, E.3    Feige, U.4    Vijayaraghavan, A.5
  • 8
    • 84860212454 scopus 로고    scopus 로고
    • Polynomial integrality gaps for strong SDP relaxations of densest k-subgraph
    • A. Bhaskara, M. Charikar, A. Vijayaraghavan, V. Guruswami, and Y. Zhou. Polynomial integrality gaps for strong sdp relaxations of densest k-subgraph. In SODA, pages 388-405, 2012.
    • (2012) SODA , pp. 388-405
    • Bhaskara, A.1    Charikar, M.2    Vijayaraghavan, A.3    Guruswami, V.4    Zhou, Y.5
  • 10
    • 0001926474 scopus 로고    scopus 로고
    • A polynomial-time algorithm for learning noisy linear threshold functions
    • A. Blum, A. M. Frieze, R. Kannan, and S. Vempala. A polynomial-time algorithm for learning noisy linear threshold functions. Algorithmica, 22(1/2):35-52, 1998.
    • (1998) Algorithmica , vol.22 , Issue.1-2 , pp. 35-52
    • Blum, A.1    Frieze, A.M.2    Kannan, R.3    Vempala, S.4
  • 11
    • 0028062299 scopus 로고
    • Weakly learning DNF and characterizing statistical query learning using fourier analysis
    • A. Blum, M. L. Furst, J. C. Jackson, M. J. Kearns, Y. Mansour, and S. Rudich. Weakly learning dnf and characterizing statistical query learning using fourier analysis. In STOC, pages 253-262, 1994.
    • (1994) STOC , pp. 253-262
    • Blum, A.1    Furst, M.L.2    Jackson, J.C.3    Kearns, M.J.4    Mansour, Y.5    Rudich, S.6
  • 14
    • 77951254878 scopus 로고    scopus 로고
    • Graph partitioning via adaptive spectral techniques
    • A. Coja-Oghlan. Graph partitioning via adaptive spectral techniques. Combinatorics, Probability & Computing, 19(2):227-284, 2010.
    • (2010) Combinatorics, Probability & Computing , vol.19 , Issue.2 , pp. 227-284
    • Coja-Oghlan, A.1
  • 15
    • 84959922759 scopus 로고    scopus 로고
    • Finding hidden cliques in linear time with high probability
    • Y. Dekel, O. Gurel-Gurevich, and Y. Peres. Finding hidden cliques in linear time with high probability. In Proceedings of ANALCO, pages 67-75, 2011.
    • (2011) Proceedings of ANALCO , pp. 67-75
    • Dekel, Y.1    Gurel-Gurevich, O.2    Peres, Y.3
  • 17
    • 41149110111 scopus 로고    scopus 로고
    • A simple polynomial-time rescaling algorithm for solving linear programs
    • J. Dunagan and S. Vempala. A simple polynomial-time rescaling algorithm for solving linear programs. Math. Program., 114(1):101-114, 2008.
    • (2008) Math. Program , vol.114 , Issue.1 , pp. 101-114
    • Dunagan, J.1    Vempala, S.2
  • 18
    • 0036290677 scopus 로고    scopus 로고
    • Relations between average case complexity and approximation complexity
    • U. Feige. Relations between average case complexity and approximation complexity. In IEEE Conference on Computational Complexity, page 5, 2002.
    • (2002) IEEE Conference on Computational Complexity , pp. 5
    • Feige, U.1
  • 19
    • 0034406149 scopus 로고    scopus 로고
    • Finding and certifying a large hidden clique in a semirandom graph
    • U. Feige and R. Krauthgamer. Finding and certifying a large hidden clique in a semirandom graph. Random Struct. Algorithms, 16(2):195-208, 2000.
    • (2000) Random Struct. Algorithms , vol.16 , Issue.2 , pp. 195-208
    • Feige, U.1    Krauthgamer, R.2
  • 20
    • 0038285474 scopus 로고    scopus 로고
    • The probable value of the Lovász-Schrijver relaxations for maximum independent set
    • U. Feige and R. Krauthgamer. The probable value of the Lovász-Schrijver relaxations for maximum independent set. SICOMP, 32(2):345-370, 2003.
    • (2003) SICOMP , vol.32 , Issue.2 , pp. 345-370
    • Feige, U.1    Krauthgamer, R.2
  • 21
    • 84879821278 scopus 로고    scopus 로고
    • Finding hidden cliques in linear time
    • U. Feige and D. Ron. Finding hidden cliques in linear time. In Proceedings of AofA, pages 189-204, 2010.
    • (2010) Proceedings of AofA , pp. 189-204
    • Feige, U.1    Ron, D.2
  • 22
    • 84861597048 scopus 로고    scopus 로고
    • A complete characterization of statistical query learning with applications to evolvability
    • V. Feldman. A complete characterization of statistical query learning with applications to evolvability. Journal of Computer System Sciences, 78(5):1444-1459, 2012.
    • (2012) Journal of Computer System Sciences , vol.78 , Issue.5 , pp. 1444-1459
    • Feldman, V.1
  • 23
    • 84868364709 scopus 로고    scopus 로고
    • Statistical algorithms and a lower bound for detecting planted cliques
    • abs/1201.1214
    • V. Feldman, E. Grigorescu, L. Reyzin, S. Vempala, and Y. Xiao. Statistical algorithms and a lower bound for detecting planted cliques. CoRR, abs/1201.1214, 2012.
    • (2012) CoRR
    • Feldman, V.1    Grigorescu, E.2    Reyzin, L.3    Vempala, S.4    Xiao, Y.5
  • 24
    • 80052351392 scopus 로고    scopus 로고
    • A new approach to the planted clique problem
    • A. M. Frieze and R. Kannan. A new approach to the planted clique problem. In FSTTCS, pages 187-198, 2008.
    • (2008) FSTTCS , pp. 187-198
    • Frieze, A.M.1    Kannan, R.2
  • 26
    • 0000844603 scopus 로고    scopus 로고
    • Some optimal inapproximability results
    • July
    • J. Hástad. Some optimal inapproximability results. J. ACM, 48:798-859, July 2001.
    • (2001) J. ACM , vol.48 , pp. 798-859
    • Hástad, J.1
  • 27
    • 77956890234 scopus 로고
    • Monte carlo sampling methods using markov chains and their applications
    • W. K. Hastings. Monte carlo sampling methods using markov chains and their applications. Biometrika, 57(1):97-109, 1970.
    • (1970) Biometrika , vol.57 , Issue.1 , pp. 97-109
    • Hastings, W.K.1
  • 28
    • 79952972547 scopus 로고    scopus 로고
    • How hard is it to approximate the best nash equilibrium?
    • E. Hazan and R. Krauthgamer. How hard is it to approximate the best nash equilibrium? SIAM J. Comput., 40(1):79-91, 2011.
    • (2011) SIAM J. Comput. , vol.40 , Issue.1 , pp. 79-91
    • Hazan, E.1    Krauthgamer, R.2
  • 29
    • 0038505858 scopus 로고    scopus 로고
    • On the efficiency of noise-tolerant PAC algorithms derived from statistical queries
    • Nov
    • J. Jackson. On the efficiency of noise-tolerant PAC algorithms derived from statistical queries. Annals of Mathematics and Artificial Intelligence, 39(3):291-313, Nov. 2003.
    • (2003) Annals of Mathematics and Artificial Intelligence , vol.39 , Issue.3 , pp. 291-313
    • Jackson, J.1
  • 30
    • 84990700795 scopus 로고
    • Large cliques elude the metropolis process
    • M. Jerrum. Large cliques elude the metropolis process. Random Struct. Algorithms, 3(4):347-360, 1992.
    • (1992) Random Struct. Algorithms , vol.3 , Issue.4 , pp. 347-360
    • Jerrum, M.1
  • 31
    • 0038501444 scopus 로고    scopus 로고
    • Hiding cliques for cryptographic security
    • A. Juels and M. Peinado. Hiding cliques for cryptographic security. Des. Codes Cryptography, 20(3):269-280, 2000.
    • (2000) Des. Codes Cryptography , vol.20 , Issue.3 , pp. 269-280
    • Juels, A.1    Peinado, M.2
  • 32
    • 84879821117 scopus 로고    scopus 로고
    • personal communication
    • R. Kannan. personal communication.
    • Kannan, R.1
  • 34
    • 0032202014 scopus 로고    scopus 로고
    • Efficient noise-tolerant learning from statistical queries
    • M. Kearns. Efficient noise-tolerant learning from statistical queries. Journal of the ACM, 45(6):983-1006, 1998.
    • (1998) Journal of the ACM , vol.45 , Issue.6 , pp. 983-1006
    • Kearns, M.1
  • 35
    • 17744389433 scopus 로고    scopus 로고
    • Ruling out ptas for graph min-bisection, densest subgraph and bipartite clique
    • S. Khot. Ruling out ptas for graph min-bisection, densest subgraph and bipartite clique. In FOCS, pages 136-145, 2004.
    • (2004) FOCS , pp. 136-145
    • Khot, S.1
  • 36
    • 26444479778 scopus 로고
    • Optimization by simmulated annealing
    • S. Kirkpatrick, D. G. Jr., and M. P. Vecchi. Optimization by simmulated annealing. Science, 220(4598):671-680, 1983.
    • (1983) Science , vol.220 , Issue.4598 , pp. 671-680
    • Kirkpatrick, S.1    Vecchi, M.P.2
  • 37
    • 0003156650 scopus 로고
    • Expected complexity of graph partitioning problems
    • L. Kucera. Expected complexity of graph partitioning problems. Discrete Applied Mathematics, 57(2-3):193-212, 1995.
    • (1995) Discrete Applied Mathematics , vol.57 , Issue.2-3 , pp. 193-212
    • Kucera, L.1
  • 38
    • 0035186726 scopus 로고    scopus 로고
    • Spectral partitioning of random graphs
    • F. McSherry. Spectral partitioning of random graphs. In FOCS, pages 529-537, 2001.
    • (2001) FOCS , pp. 529-537
    • McSherry, F.1
  • 41
    • 0001454867 scopus 로고
    • On the criterion that a given system of deviations from the probable in the case of a correlated system of variables is such that it can be reasonably supposed to have arisen from random sampling
    • Series 5
    • K. Pearson. On the criterion that a given system of deviations from the probable in the case of a correlated system of variables is such that it can be reasonably supposed to have arisen from random sampling. Philosophical Magazine, Series 5, 50(302):157-175, 1900.
    • (1900) Philosophical Magazine , vol.50 , Issue.302 , pp. 157-175
    • Pearson, K.1
  • 43
    • 0034140159 scopus 로고    scopus 로고
    • Computational sample complexity and attribute-efficient learning
    • R. Servedio. Computational sample complexity and attribute-efficient learning. Journal of Computer and System Sciences, 60(1):161-178, 2000.
    • (2000) Journal of Computer and System Sciences , vol.60 , Issue.1 , pp. 161-178
    • Servedio, R.1
  • 44
    • 77952015400 scopus 로고    scopus 로고
    • Characterizing statistical query learning: Simplified notions and proofs
    • B. Szörényi. Characterizing statistical query learning: Simplified notions and proofs. In ALT, pages 186-200, 2009.
    • (2009) ALT , pp. 186-200
    • Szörényi, B.1
  • 45
    • 84950758368 scopus 로고
    • The calculation of posterior distributions by data augmentation (with discussion)
    • M. Tanner and W. Wong. The calculation of posterior distributions by data augmentation (with discussion). Journal of the American Statistical Association, 82:528-550, 1987.
    • (1987) Journal of the American Statistical Association , vol.82 , pp. 528-550
    • Tanner, M.1    Wong, W.2
  • 46
    • 0021518106 scopus 로고
    • A theory of the learnable
    • L. G. Valiant. A theory of the learnable. Commun. ACM, 27(11):1134-1142, 1984.
    • (1984) Commun. ACM , vol.27 , Issue.11 , pp. 1134-1142
    • Valiant, L.G.1
  • 47
    • 0001024505 scopus 로고
    • On the uniform convergence of relative frequencies of events to their probabilities
    • V. Vapnik and A. Chervonenkis. On the uniform convergence of relative frequencies of events to their probabilities. Theory of Probab. and its Applications, 16(2):264-280, 1971.
    • (1971) Theory of Probab. and its Applications , vol.16 , Issue.2 , pp. 264-280
    • Vapnik, V.1    Chervonenkis, A.2
  • 48
    • 0021819411 scopus 로고
    • Thermodynamical approach to the traveling salesman problem: An efficient simulation algorithm
    • Jan
    • V. Černý. Thermodynamical approach to the traveling salesman problem: An efficient simulation algorithm. Journal of Optimization Theory and Applications, 45(1):41-51, Jan. 1985.
    • (1985) Journal of Optimization Theory and Applications , vol.45 , Issue.1 , pp. 41-51
    • Černý, V.1
  • 49
    • 84948123449 scopus 로고    scopus 로고
    • On learning correlated boolean functions using statistical queries
    • K. Yang. On learning correlated boolean functions using statistical queries. In Proceedings of ALT, pages 59-76, 2001.
    • (2001) Proceedings of ALT , pp. 59-76
    • Yang, K.1
  • 50
    • 17444425308 scopus 로고    scopus 로고
    • New lower bounds for statistical query learning
    • K. Yang. New lower bounds for statistical query learning. J. Comput. Syst. Sci., 70(4):485-509, 2005.
    • (2005) J. Comput. Syst. Sci. , vol.70 , Issue.4 , pp. 485-509
    • Yang, K.1
  • 51
    • 85026748110 scopus 로고
    • Probabilistic computations: Toward a unified measure of complexity
    • A. Yao. Probabilistic computations: Toward a unified measure of complexity. In FOCS, pages 222-227, 1977.
    • (1977) FOCS , pp. 222-227
    • Yao, A.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.