Yuri Kalnishkan
- CBFH+97.N. Cesa-Bianchi, Y. Freund, D. Haussler, D. P. Helmbold, R. E. Schapire, and M. K. Warmuth. How to use expert advice. Journal of the ACM, (44):427-485, 1997. Google Scholar
Digital Library
- Cou48.R. Courant. Differential and Integral Calculus, volume 1. Blackie & Son, Ltd, London and Glasgo, 1948.Google Scholar
- HKW94.D. Haussler, J. Kivinen, and M. K. Warmuth. Tight worst-case loss bounds for predicting with expert advise. Technical Report UCSC- CRL-94-36, University of California at Santa Cruz, revised December 1994. Google ScholarDigital Library
- Hsi81.Chuan-Chin Hsiung. A First Course in Differential Geometry. John Wiley & Sons, Inc, 1981.Google Scholar
- LV97.M. Li and P. Viffmyi. An Introduction to Kolmogorov Complexity and Its Applications. Springer, New York, 2nd edition, 1997. Google ScholarDigital Library
- LW94.N. Littlestone and M. K. Warmuth. The weighted majority algorithm. Information and Computation, 108:212-261, 1994. Google ScholarDigital Library
- VG99.V. Vovk and A. Gammerman. Complexity eValuation principle. Technical report, Royal Holloway, University of London, 1999.Google Scholar
- Vov90.V. Vovk. Aggregating strategies. In M. Fulk and J. Case, editors, Proceedings of the 3rd Annual Workshop on Computational Learning Theory, pages 371-383, San Mateo, CA, 1990. Morgan Kaufmann. Google ScholarDigital Library
- Vov97.V. Vovk. Probability theory for the Brier game. In M. Li and A. Mamoka, editors, Algorithmic Learning Theory, volume 1316 of Lecture Notes in Computer Science, pages 323-338. 1997. To appear in Theoretical Computer Science. Google ScholarDigital Library
- Vov98.V Vovk. A game of prediction with expert advice. Journal of Computer and System Sciences, (56): 153-173, 1998. Google ScholarDigital Library
- VW98.V. Vovk and C. J. H. C. Watkins. Universal portfolio selection. In Proceedings of the l l th Annual Conference on Computational Learning Theory, pages 12-23, 1998. Google ScholarDigital Library
- V’y94.V.V. V'yugin. Algorithmic entropy (complexity) of finite objects and its applications to defining randomness and amount of information. Selecta Mathematica formerly Sovietica, 13:357-389, 1994.Google Scholar
- ZL70.A.K. Zvonkin and L. A. Levin. The complexity of finite objects and the development of the concepts of information and randomness by means of the theory of algorithms. Russian Math. Surveys, 25:83-124, 1970.Google ScholarCross Ref
Index Terms
- Linear relations between square-loss and Kolmogorov complexity
Recommendations
Kolmogorov Complexity for Possibly Infinite Computations
In this paper we study the Kolmogorov complexity for non-effective computations, that is, either halting or non-halting computations on Turing machines. This complexity function is defined as the length of the shortest input that produce a desired ...
An Additivity Theorem for Plain Kolmogorov Complexity
We prove the formula C(a,b)=K(a|C(a,b))+C(b|a,C(a,b))+O(1) that expresses the plain complexity of a pair in terms of prefix-free and plain conditional complexities of its components.
Comments