Lazy paired hyper-parameter tuning

IJCAI International Joint Conference on Artificial Intelligence

Volumn , Issue , 2013, Pages 1924-1931

  Zheng, Alice X ^a   Bilenko, Mikhail ^a  

^a MICROSOFT RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CONTINUOUS PARAMETERS; CROSS VALIDATION; DISCRETE PARAMETERS; MACHINE LEARNING APPLICATIONS; MINIMIZING THE NUMBER OF; PREDICTIVE ACCURACY; REAL-WORLD DATASETS; STATE-OF-THE-ART TECHNIQUES;

ARTIFICIAL INTELLIGENCE;

EID: 84896063035     PISSN: 10450823     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (24)

1. P. Auer, N. Cesa-Bianchi, Y. Freund, and R. Schapire. The nonstochastic multiarmed ban dit problem. SIAM Journal on Computing, 32(1):48-77, 2002.
2. Peter Auer, Nicol Cesa-Bianchi, and Paul Fischer. Finite-time analysis of the multiarmed bandit problem. Machine Learning, 47:235-256, 2002.
3. James Bergstra and Yoshua Bengio. Random search for hyper-parameter optimization. Journal of Machine Learning Research, 13:281-305, Feb 2012.
4. 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. arXiv preprint arXiv:1012.2599, 2010.
5. A.R. Conn, K. Scheinberg, and L.N. Vicente. Introduction to derivative-free optimization. MPSSIAM series on optimization. Society for Industrial and Applied Mathematics/Mathematical Programming Society, 2009.
6. G. Dror, N. Koenigstein, and Y. Koren. Yahoo! music recommendations: Modeling music ratings with temporal dynamics and item taxonomy. In Proceedings of RecSys, 2011.
7. J. Friedman. Greedy function approximation: a gradient boosting machine. Annals of Statistics, 25(5):1189-1232, 2001.
8. J. Gittins, K. Glazebrook, and R. Weber. Multi-armed bandit allocation indices. Wiley, 2011.
9. Russell Greiner. Probabilistic hill-climbing: Theory and applications. In Proceedings of the Ninth Canadian Conference on Artificial Intelligence (CSCSI- 92), pages 60-67. Morgan Kaufmann Publishers, Inc, 1992.
10. N. Hansen and A. Ostermeier. Adapting arbitrary normal mutation distributions in evolution strategies: The covariance matrix adaptation. In Evolutionary Computation, 1996., Proceedings of IEEE International Conference on, pages 312-317. IEEE, 1996.
11. Verena Heidrich-Meisner and Christian Igel. Hoeffding and Bernstein races for selecting policies in evolutionary direct policy search. In Proceedings of the 26th Annual International Conference on Machine Learning, ICML '09, pages 401-408, New York, NY, USA, 2009. ACM.
12. F. Hutter, H. Hoos, and K. Leyton- Brown. Sequential model-based optimization for general algorithm configuration. Learning and Intelligent Optimization, pages 507-523, 2011.
13. Tammo Krueger, Danny Panknin, and Mikio Braun. Fast cross-validation via sequential testing. arxiv CoRR, abs/1206.2248, 2012.
14. T.L. Lai and H. Robbins. Asymptotically efficient adaptive allocation rules. Advances in Applied Mathematics, 6:4-22, 1985.
15. E. L. Lehmann and Joseph P. Romano. Testing statistical hypotheses. Springer Texts in Statistics. Springer, New York, third edition, 2005.
16. M.A. Luersen, R. Le Riche, and F. Guyon. A constrained, globalized, and bounded Nelder- Mead method for engineering optimization. Structural and Multidisciplinary Optimization, 27(1):43-54, 2004.
17. Oded Maron and Andrew Moore. Hoeffding races: Accelerating model selection search for classification and function approximation. In Advances in Neural Information Processing Systems, volume 6, pages 59-66, 1994.
18. J. A. Nelder and R. Mead. A simplex method for function minimization. Computer Journal, 7:308-313, 1965.
19. Juliet Popper Shaffer. Multiple hypothesis testing. Annual review of psychology, 46(1):561-584, 1995.
20. J.C. Spall. Introduction to stochastic search and optimization: estimation, simulation, and control, volume 64. Wiley-Interscience, 2003.
21. Nathan Srebro and Ambuj Tewari. Stochastic Optimization: ICML 2010 Tutorial, 2010.
22. M.J.A. Strens and A.W. Moore. Policy search using paired comparisons. Journal of Machine Learning Research, 3(1):921-950, 2002.
23. Shulin Yang and Ali Rahimi. Structure learning for optimization. In J. Shawe-Taylor, R.S. Zemel, P. Bartlett, F.C.N. Pereira, and K.Q. Weinberger, editors, Advances in Neural Information Processing Systems 24, pages 1044-1052. MIT Press, 2011.
24. Y. Yue, J. Broder, R. Kleinberg, and T. Joachims. The K-armed dueling bandits problem. Journal of Computer and System Sciences, 2012.