Prediction with expert advice under discounted loss

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6331 LNAI, Issue , 2010, Pages 255-269

  Chernov, Alexey ^a   Zhdanov, Fedor ^a  

^a UNIVERSITY OF LONDON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

DISCOUNTED LOSS; PREDICTION WITH EXPERT ADVICE; WEIGHTED AVERAGES;

ALGORITHMS;

EID: 78249273922     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-16108-7_22     Document Type: Conference Paper

References (22)

1. Beckenbach, E.F., Bellman, R.: Inequalities. Springer, Berlin (1961)
2. Cesa-Bianchi, N., Lugosi, G.: Prediction, learning, and games. Cambridge University Press, Cambridge (2006)
3. Chaudhuri, K., Freund, Y., Hsu, D.: A parameter-free hedging algorithm. In: Advances in Neural Information Processing Systems, vol. 22, pp. 297-305 (2009)
4. Chernov, A., Kalnishkan, Y., Zhdanov, F., Vovk, V.: Supermartingales in prediction with expert advice. Theoretical Computer Science 411, 2647-2669 (2010); See also: arXiv:1003.2218 [cs.LG]
5. Chernov, A., Vovk, V.: Prediction with advice of unknown number of experts. In: Proc. of 26th Conf. on Uncertainty in Artificial Intelligence, pp. 117-125 (2010); See also: arXiv:1006.0475 [cs.LG]
6. Chernov, A., Zhdanov, F.: Prediction with expert advice under discounted loss. Technical report, arXiv:1005.1918v1 [cs.LG] (2010)
7. Freund, Y., Hsu, D.: A new hedging algorithm and its application to inferring latent random variables. Technical report, arXiv:0806.4802v1 [cs.GT] (2008)
8. Gammerman, A., Kalnishkan, Y., Vovk, V.: On-line prediction with kernels and the complexity approximation principle. In: Proc. of 20th Conf. on Uncertainty in Artificial Intelligence, pp. 170-176 (2004)
9. Gardner, E.S.: Exponential smoothing: The state of the art - part II. International Journal of Forecasting 22, 637-666 (2006)
10. Harville, D.A.: Matrix algebra from a statistician's perspective. Springer, Heidelberg (1997)
11. Haussler, D., Kivinen, J., Warmuth, M.: Sequential prediction of individual sequences under general loss functions. IEEE Transactions on Information Theory 44, 1906-1925 (1998) (Pubitemid 128738560)
12. Herbster, M., Warmuth, M.K.: Tracking the best expert. Machine Learning 32, 151-178 (1998)
13. Kalnishkan, Y., Vyugin, M.: The weak aggregating algorithm and weak mixability. Technical report, CLRC-TR-03-01 (2003)
14. Kalnishkan, Y., Vyugin, M.: The weak aggregating algorithm and weak mixability. Journal of Computer and System Sciences 74(8), 1228-1244 (2008)
15. Muth, J.F.: Optimal properties of exponentially weighted forecasts. Journal of the American Statistical Association 55, 299-306 (1960)
16. Schölkopf, B., Smola, A.J.: Learning with kernels: Support Vector Machines, regularization, optimization, and beyond. MIT Press, Cambridge (2002)
17. Sutton, R., Barto, A.: Reinforcement learning: An introduction. MIT Press, Cambridge (1998)
18. Vovk, V.: Aggregating strategies. In: Proc. of 3rd COLT, pp. 371-383 (1990)
19. Vovk, V.: A game of prediction with expert advice. Journal of Computer and System Sciences 56, 153-173 (1998)
20. Vovk, V.: Derandomizing stochastic prediction strategies. Machine Learning 35, 247-282 (1999)
21. Vovk, V.: Competitive on-line statistics. Int. Stat. Review 69, 213-248 (2001)
22. Vovk, V.: On-line regression competitive with reproducing kernel Hilbert spaces. Technical report, arXiv:cs/0511058 [cs.LG] (2005)