Title :
On sequential universal coding of sequences with limited amount of training data
Author :
Sutskover, I. ; Ziv, J.
Abstract :
The problem of universal coding in the non-asymptotic regime is investigated. In a forthcoming paper, some non-asymptotic lower bounds on the achievable compression are proven by Ziv for the class of stationary sources and a class of admissible algorithms. To these lower bounds we match an achievable upper bound by construction of a proper algorithm. We also extend our results to a case where some prior assumptions can be incorporated into universal algorithms, creating algorithms that are “almost universal”
Keywords :
data compression; sequences; source coding; admissible algorithms; data compression; nonasymptotic lower bounds; nonasymptotic regime; sequential universal coding; source sequence coding; stationary sources; training data; universal algorithms; Algorithm design and analysis; Compression algorithms; Encoding; Entropy; Minimax techniques; Pixel; Random variables; Statistics; Training data; Upper bound;
Conference_Titel :
Electrical and electronic engineers in israel, 2000. the 21st ieee convention of the
Conference_Location :
Tel-Aviv
Print_ISBN :
0-7803-5842-2
DOI :
10.1109/EEEI.2000.924431