메뉴 건너뛰기




Volumn , Issue , 2013, Pages 1778-1784

Bayesian optimization in high dimensions via random embeddings

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMATIC ALGORITHMS; BAYESIAN OPTIMIZATION; CONTINUOUS VARIABLES; HIGH DIMENSIONS; HIGH-DIMENSIONAL PROBLEMS; INTELLIGENT USER INTERFACES; MIXED INTEGER LINEAR PROGRAMMING; SENSOR PLACEMENT;

EID: 84896058897     PISSN: 10450823     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (295)

References (35)
  • 2
    • 84857855190 scopus 로고    scopus 로고
    • Random search for hyper-parameter optimization
    • J. Bergstra and Y. Bengio. Random search for hyper-parameter optimization. JMLR, 13:281-305, 2012.
    • (2012) JMLR , vol.13 , pp. 281-305
    • Bergstra, J.1    Bengio, Y.2
  • 3
    • 85162384813 scopus 로고    scopus 로고
    • Algorithms for hyper-parameter optimization
    • J. Bergstra, R. Bardenet, Y. Bengio, and B. Kégl. Algorithms for hyper-parameter optimization. In NIPS, pages 2546-2554, 2011.
    • (2011) NIPS , pp. 2546-2554
    • Bergstra, J.1    Bardenet, R.2    Bengio, Y.3    Kégl, B.4
  • 4
    • 84896063352 scopus 로고    scopus 로고
    • Making a science of model search
    • abs/1209.5111
    • J. Bergstra, D. Yamins, and D. D. Cox. Making a science of model search. CoRR, abs/1209.5111, 2012.
    • (2012) CoRR
    • Bergstra, J.1    Yamins, D.2    Cox, D.D.3
  • 5
    • 77958068642 scopus 로고    scopus 로고
    • A tutorial on Bayesian optimization of expensive cost functions, with application to active user modeling and hierarchical reinforcement learning
    • and arXiv:1012.2599v1, Dept. of Computer Science, University of British Columbia
    • E. Brochu, V. M. Cora, and N. de Freitas. A tutorial on Bayesian optimization of expensive cost functions, with application to active user modeling and hierarchical reinforcement learning. Technical Report UBC TR-2009-23 and arXiv:1012.2599v1, Dept. of Computer Science, University of British Columbia, 2009.
    • (2009) Technical Report UBC TR-2009-23
    • Brochu, E.1    Cora, V.M.2    De Freitas, N.3
  • 6
    • 80555140070 scopus 로고    scopus 로고
    • Convergence rates of efficient global optimization algorithms
    • A. D. Bull. Convergence rates of efficient global optimization algorithms. JMLR, 12:2879-2904, 2011.
    • (2011) JMLR , vol.12 , pp. 2879-2904
    • Bull, A.D.1
  • 7
    • 84896062989 scopus 로고    scopus 로고
    • Bandit theory meets compressed sensing for high dimensional stochastic linear bandit
    • A. Carpentier and R. Munos. Bandit theory meets compressed sensing for high dimensional stochastic linear bandit. In AIStats, pages 190-198, 2012.
    • (2012) AIStats , pp. 190-198
    • Carpentier, A.1    Munos, R.2
  • 8
    • 84867136616 scopus 로고    scopus 로고
    • Joint optimization and variable selection of high-dimensional Gaussian processes
    • B. Chen, R.M. Castro, and A. Krause. Joint optimization and variable selection of high-dimensional Gaussian processes. In ICML, 2012.
    • (2012) ICML
    • Chen, B.1    Castro, R.M.2    Krause, A.3
  • 9
    • 84867124523 scopus 로고    scopus 로고
    • Exponential regret bounds for Gaussian process bandits with deterministic observations
    • N. de Freitas, A. Smola, and M. Zoghi. Exponential regret bounds for Gaussian process bandits with deterministic observations. In ICML, 2012.
    • (2012) ICML
    • De Freitas, N.1    Smola, A.2    Zoghi, M.3
  • 10
    • 44649111994 scopus 로고    scopus 로고
    • Connections in networks: A hybrid approach
    • C. P. Gomes, W.J. van Hoeve, and A. Sabharwal. Connections in networks: A hybrid approach. In CPAIOR, volume 5015, pages 303-307, 2008.
    • (2008) CPAIOR , vol.5015 , pp. 303-307
    • Gomes, C.P.1    Van Hoeve, W.J.2    Sabharwal, A.3
  • 11
    • 0035377566 scopus 로고    scopus 로고
    • Completely derandomized self-adaptation in evolution strategies
    • N. Hansen and A. Ostermeier. Completely derandomized self-adaptation in evolution strategies. Evol. Comput., 9(2):159-195, 2001.
    • (2001) Evol. Comput. , vol.9 , Issue.2 , pp. 159-195
    • Hansen, N.1    Ostermeier, A.2
  • 12
    • 80053160717 scopus 로고    scopus 로고
    • Portfolio allocation for Bayesian optimization
    • M. Hoffman, E. Brochu, and N. de Freitas. Portfolio allocation for Bayesian optimization. In UAI, pages 327-336, 2011.
    • (2011) UAI , pp. 327-336
    • Hoffman, M.1    Brochu, E.2    De Freitas, N.3
  • 13
    • 84856827305 scopus 로고    scopus 로고
    • Programming by optimization
    • H. H. Hoos. Programming by optimization. Commun. ACM, 55(2):70-80, 2012.
    • (2012) Commun. ACM , vol.55 , Issue.2 , pp. 70-80
    • Hoos, H.H.1
  • 14
    • 77955439544 scopus 로고    scopus 로고
    • Automated configuration of mixed integer programming solvers
    • F. Hutter, H. H. Hoos, and K. Leyton-Brown. Automated configuration of mixed integer programming solvers. In CPAIOR, pages 186-202, 2010.
    • (2010) CPAIOR , pp. 186-202
    • Hutter, F.1    Hoos, H.H.2    Leyton-Brown, K.3
  • 15
    • 84868554032 scopus 로고    scopus 로고
    • Sequential model-based optimization for general algorithm configuration
    • F. Hutter, H. H. Hoos, and K. Leyton-Brown. Sequential model-based optimization for general algorithm configuration. In LION, pages 507-523, 2011.
    • (2011) LION , pp. 507-523
    • Hutter, F.1    Hoos, H.H.2    Leyton-Brown, K.3
  • 16
    • 84867862661 scopus 로고    scopus 로고
    • Parallel algorithm configuration
    • F. Hutter, H. H. Hoos, and K. Leyton-Brown. Parallel algorithm configuration. In LION, pages 55-70, 2012.
    • (2012) LION , pp. 55-70
    • Hutter, F.1    Hoos, H.H.2    Leyton-Brown, K.3
  • 17
    • 84896062698 scopus 로고    scopus 로고
    • Identifying key algorithm parameters and instance features using forward selection
    • F. Hutter, H. Hoos, and K. Leyton-Brown. Identifying key algorithm parameters and instance features using forward selection. In LION, 2013.
    • (2013) LION
    • Hutter, F.1    Hoos, H.2    Leyton-Brown, K.3
  • 20
    • 0000561424 scopus 로고    scopus 로고
    • Efficient global optimization of expensive black-box functions
    • D.R. Jones, M. Schonlau, and W.J. Welch. Efficient global optimization of expensive black-box functions. J. of Global optimization, 13(4):455-492, 1998.
    • (1998) J. of Global Optimization , vol.13 , Issue.4 , pp. 455-492
    • Jones, D.R.1    Schonlau, M.2    Welch, W.J.3
  • 21
    • 0035577808 scopus 로고    scopus 로고
    • A taxonomy of global optimization methods based on response surfaces
    • D.R. Jones. A taxonomy of global optimization methods based on response surfaces. J. of Global Optimization, 21(4):345-383, 2001.
    • (2001) J. of Global Optimization , vol.21 , Issue.4 , pp. 345-383
    • Jones, D.R.1
  • 22
    • 84896062990 scopus 로고    scopus 로고
    • An experimental methodology for response surface optimization methods
    • D. Lizotte, R. Greiner, and D. Schuurmans. An experimental methodology for response surface optimization methods. J. of Global Optimization, pages 1-38, 2011.
    • (2011) J. of Global Optimization , pp. 1-38
    • Lizotte, D.1    Greiner, R.2    Schuurmans, D.3
  • 24
    • 70349325516 scopus 로고    scopus 로고
    • A Bayesian exploration-exploitation approach for optimal online sensing and planning with a visually guided mobile robot
    • R. Martinez-Cantin, N. de Freitas, E. Brochu, J. Castellanos, and A. Doucet. A Bayesian exploration-exploitation approach for optimal online sensing and planning with a visually guided mobile robot. Autonomous Robots, 27(2):93-103, 2009.
    • (2009) Autonomous Robots , vol.27 , Issue.2 , pp. 93-103
    • Martinez-Cantin, R.1    De Freitas, N.2    Brochu, E.3    Castellanos, J.4    Doucet, A.5
  • 25
    • 84896063378 scopus 로고    scopus 로고
    • Bayesian approach for randomization of heuristic algorithms of discrete programming
    • J. Močkus, A. Močkus, and L. Močkus. Bayesian approach for randomization of heuristic algorithms of discrete programming. American Math. Society, 1999.
    • (1999) American Math. Society
    • Močkus, J.1    Močkus, A.2    Močkus, L.3
  • 26
    • 84867137347 scopus 로고
    • The Bayesian approach to global optimization
    • Springer
    • J. Močkus. The Bayesian approach to global optimization. In Systems Modeling and Optimization, volume 38, pages 473-481. Springer, 1982.
    • (1982) Systems Modeling and Optimization , vol.38 , pp. 473-481
    • Močkus, J.1
  • 27
    • 0012499686 scopus 로고
    • Application of Bayesian approach to numerical methods of global and stochastic optimization
    • J. Močkus. Application of Bayesian approach to numerical methods of global and stochastic optimization. J. of Global Optimization, 4(4):347-365, 1994.
    • (1994) J. of Global Optimization , vol.4 , Issue.4 , pp. 347-365
    • Močkus, J.1
  • 28
    • 77956033531 scopus 로고    scopus 로고
    • Gaussian processes for global optimisation
    • M. A. Osborne, R. Garnett, and S. J. Roberts. Gaussian processes for global optimisation. In LION, 2009.
    • (2009) LION
    • Osborne, M.A.1    Garnett, R.2    Roberts, S.J.3
  • 31
    • 84869201485 scopus 로고    scopus 로고
    • Practical Bayesian optimization of machine learning algorithms
    • J. Snoek, H. Larochelle, and R. P. Adams. Practical Bayesian optimization of machine learning algorithms. In NIPS, 2012.
    • (2012) NIPS
    • Snoek, J.1    Larochelle, H.2    Adams, R.P.3
  • 32
    • 77956501313 scopus 로고    scopus 로고
    • Gaussian process optimization in the bandit setting: No regret and experimental design
    • N. Srinivas, A. Krause, S. M. Kakade, and M. Seeger. Gaussian process optimization in the bandit setting: No regret and experimental design. In ICML, 2010.
    • (2010) ICML
    • Srinivas, N.1    Krause, A.2    Kakade, S.M.3    Seeger, M.4
  • 33
    • 84867847475 scopus 로고    scopus 로고
    • Generating fast domain-optimized planners by automatically configuring a generic parameterised planner
    • M. Vallati, C. Fawcett, A. E. Gerevini, H. H. Hoos, and A. Saetti. Generating fast domain-optimized planners by automatically configuring a generic parameterised planner. In ICAPS-PAL, 2011.
    • (2011) ICAPS-PAL
    • Vallati, M.1    Fawcett, C.2    Gerevini, A.E.3    Hoos, H.H.4    Saetti, A.5


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.