@article{571d0ccffd334e3a86286197a93df798,
title = "A Strong Version of the Redundancy-Capacity Theorem of Universal Coding",
abstract = "The capacity of the channel induced by a given class of sources is well known to be an attainable lower bound on the redundancy of universal codes with respect to this class, both in the minimax sense and in the Bayesian (maximin) sense. We show that this capacity is essentially a lower bound also in a stronger sense, that is, for “most” sources in the class. This result extends Rissanen's lower bound for parametric families. We demonstrate the applicability of this result in several examples, e.g., parametric families with growing dimensionality, piecewise-fixed sources, arbitrarily varying sources, and noisy samples of learnable functions. Finally, we discuss implications of our results to statistical inference.",
keywords = "Universal coding, arbitrarily varying sources, channel capacity, minimax redundancy, minimum description length, random coding",
author = "Neri Merhav and Meir Feder",
note = "Funding Information: Manuscript received December 15, 1993; revised July 6, 1994. This research was supported by the Wolfson Research Awards administrated by the Israel Academy of Science and Humanities. Part of this research was done while one of the authors (M.Feder) visited Sonderforschungsbereich 343, “Diskrete Strukturen in der Mathematik,” Universitat Bielefeld, Bielefeld, Germany. The material in this paper was presented at the IEEE/IMS Workshop on Information Theory and Statistics, Alexandria, VA, October 1994.",
year = "1995",
month = may,
doi = "10.1109/18.382017",
language = "אנגלית",
volume = "41",
pages = "714--722",
journal = "IEEE Transactions on Information Theory",
issn = "0018-9448",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "3",
}