A variational free energy minimization interpretation of multiuser detection in CDMA
Why this work is in the frame
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Bibliographic record
Abstract
We propose a unified approach for deriving and studying multiuser detection algorithms using the concept of variational free energy minimization. Under this generalized framework, we readily arrive at many popular multiuser detection schemes. In addition to its systematic appeal, there are several other advantages of this viewpoint. First of all, by condensing the design of multiuser detectors into the selection of a few key probability distributions, namely p(b), p(r|b) and Q(b), we provide rigorous justifications for numerous detectors that were proposed on heuristic grounds and recommend new and improved designs. Furthermore, the free energy formulation facilitates convenient joint detection and decoding (utilizing the turbo principle) when error-control codes are incorporated, as well as efficient parameter estimation via the variational expectation maximization (EM) algorithm.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.005 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it