Universal prediction of individual binary sequences in the presence of noise

IEEE Transactions on Information Theory

Volumn 47, Issue 6, 2001, Pages 2151-2173

  Weissman, Tsachy ^a,b   Merhav, Neri ^a,b  

^a IEEE   (Israel)

^b TECHNION ISRAEL INSTITUTE OF TECHNOLOGY   (Israel)

Author keywords

Expert advice; Individual sequences; Martingales; Prediction with noise; Universal prediction

Indexed keywords

INDIVIDUAL SEQUENCES; UNIVERSAL PREDICTION;

ARTIFICIAL INTELLIGENCE; GAME THEORY; INFORMATION THEORY; PROBLEM SOLVING; SPURIOUS SIGNAL NOISE;

BINARY SEQUENCES;

EID: 0035443342     PISSN: 00189448     EISSN: None     Source Type: Journal    
DOI: 10.1109/18.945240     Document Type: Article

References (51)

1. Universal algorithms for sequential decision in the presence of noisy observations
2. On sequential prediction of individual sequences relative to a set of experts
3. How to use expert advice
4. Universal portfolios
5. Universal noiseless coding
6. Prequential data analysis
7. Prequential probability: Principles and properties
8. Hierarchical universal coding
9. Universal prediction of individual sequences
10. Source coding with side information and universal coding
11. Asymptotic solutions of the compound decision problem for two completely specified distributions
12. Sequential prediction of individual sequences under general loss functions
13. Probability inequalities for sums of bounded random variables
14. A zero-delay sequential scheme for lossy coding of individual sequences
15. Universal prediction
16. Universal coding with minimum probability of codeword length overflow
17. A strong version of the redundancy-capacity theorem of universal coding
18. The κ-extended set-compound estimation problem in non-regular family of distributions
19. Worst case prediction over sequences under log loss
20. A general class of exponential inequalities for martingales and ratios
21. Asymptotics via empirical processes
22. The functional law of the iterated logarithm for stationary strongly mixing sequences
23. Universal coding, information, prediction, and estimation
24. Fisher information and stochastic complexity
25. Asymptotically subminimax solutions of compound statistical decision problems
26. Encoding a source with unknown but ordered probabilities
27. The sequential compound decision problem with m × n finite loss matrix
28. Asymptotic solutions of the sequential compound decision problem
29. Convergence of the losses of certain decision rules for the sequential compound decision problem
30. A martingale analog of Kolmogorov's law of the iterated logarithm
31. The Hartman-Wintner law of the iterated logarithm for martingales
32. Sharper bounds for Gaussian and empirical processes
33. On the uniform convergence of relative frequencies of events to their probabilities
34. Admissible solutions of κ-extended finite state set and the sequence compound decision problems
35. A game of prediction with expert advice
36. Aggregating strategies
37. Optimal sequential probability assignment for individual sequences
38. On prediction in the presence of noise
39. On prediction of individual sequences relative to a set of experts in the presence of noise
40. Universal prediction of individual binary sequences in the presence of arbitrarily varying, memoryless additive noise
41. Universal prediction of individual binary sequences in the presence of noise
42. On limited-delay lossy coding and filtering of individual sequences
43. Moderate deviations of dependent random variables related to CLT
44. Large deviations, moderate deviations and LIL for empirical processes
45. Universal filtering of individual sequences corrupted by noise
46. A zero-delay sequential scheme for lossy coding of individual sequences