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Record W2178984881 · doi:10.1109/tit.2005.856948

The Universality of Grammar-Based Codes for Sources With Countably Infinite Alphabets

2005· article· en· W2178984881 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Transactions on Information Theory · 2005
Typearticle
Languageen
FieldComputer Science
TopicAlgorithms and Data Compression
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMathematicsAlphabetCombinatoricsUniversality (dynamical systems)Discrete mathematicsCountable setLambdaGrammarPhysicsLinguistics

Abstract

fetched live from OpenAlex

In this paper, we investigate the performance of grammar-based codes for sources with countably infinite alphabets. Let /spl Lambda/ denote an arbitrary class of stationary, ergodic sources with a countably infinite alphabet. It is shown that grammar-based codes can be modified so that they are universal with respect to any /spl Lambda/ if and only if there exists a universal code for /spl Lambda/. Moreover, upper bounds on the worst case redundancies of grammar-based codes among large sets of length-n individual sequences from a countably infinite alphabet are established. Depending upon the conditions satisfied by length-n individual sequences, these bounds range from O(loglogn/logn) to O(1/log/sup 1-/spl alpha//n) for some 0</spl alpha/<1. These results complement the previous universality and redundancy results in the literature on the performance of grammar-based codes for sources with finite alphabets.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.969
Threshold uncertainty score0.340

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.220
Teacher spread0.212 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it