Dynamic Huffman coding

TL;DR: LOCO-I as discussed by the authors is a low complexity projection of the universal context modeling paradigm, matching its modeling unit to a simple coding unit, which is based on a simple fixed context model, which approaches the capability of more complex universal techniques for capturing high-order dependencies.

TL;DR: This work gives a simple approach for doing nearly as well as the best single decision, where the best is chosen with the benefit of hindsight, and these follow-the-leader style algorithms extend naturally to a large class of structured online problems for which the exponential algorithms are inefficient.

TL;DR: A variety of data compression methods are surveyed, from the work of Shannon, Fano, and Huffman in the late 1940s to a technique developed in 1986, which has important application in the areas of file storage and distributed systems.

TL;DR: It is shown that a very simple idea, used in Hannan's seminal 1957 paper, gives efficient solutions to all of these problems, including a (1+∈)-competitive algorithm as well as a lazy one that rarely switches between decisions.

TL;DR: A minimum-redundancy code is one constructed in such a way that the average number of coding digits per message is minimized.

TL;DR: Four new results about Huffman codes are presented and a simple algorithm for adapting a Huffman code to slowly varying esthnates of the source probabilities is presented.