ANALYSIS AND APPROXIMATION THEORY SEMINAR UNIVERSITY OF ALBERTA Construction of compactly supported biorthogonal wavelets in L 2 (IR s
Bibliographic record
Abstract
: This paper presents a general construction of compactly supported biorthogonal wavelets in L 2 (IR s ). In particular, a concrete method for the construction of bivariate compactly supported biorthogonal wavelets of increasing smoothness is provided. Several examples are computed. The estimate of smoothness of those examples are given based on criteria established in [RiS3]. AMS Subject Classification: Primary 45A05, 65D05, 65D15, 26B05 Secondary 41A15, 41A63 Keywords: multivariate biorthogonal wavelets, multivariate wavelets, box splines, matrix extension y Research supported in part by NSERC Canada under Grant # A7687 1 1. Introduction The present paper is the fourth of our series of papers on the construction of multivariate wavelets by using box splines. In the first paper [RiS1], we constructed exponentially decaying orthogonal wavelets from box splines for the case s = 2; 3. In [RiS2], we constructed compactly supported pre-wavelets from box splines for the case s = 1; 2; ...
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".