A Generalized Water-Filling Algorithm with Linear Complexity and Finite Convergence Time
Why this work is in the frame
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Bibliographic record
Abstract
This letter presents an algorithm with linear complexity and finite convergence time for solving the generalized water-filling (WF) problem. The WF problem is generalized by using a weighted-sum-rate, weighted-sum-power, and peak power constraints. The proposed algorithm solves the optimization problems with concave (power and rate) or quasi-concave (energy-efficiency) objective functions. Additionally, it can simultaneously use maximum-power and minimum-rate constraints and give a priority to one of the constraints in the event they generate an infeasible region. Through this generalization, the algorithm can be applied to many WF-based methods proposed in the literature. Moreover, this letter shows multiple ways to further reduce the computational complexity and, via simulation, illustrates the effectiveness of the proposed 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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 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