Exact separation of \(k\)-projection polytope constraints
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Bibliographic record
Abstract
A critical step of any cutting plane algorithm is to find valid inequalities, or more generally valid constraints, that improve the current relaxation of the integer-constrained problem. We consider the k-projection polytope constraints that are a family of constraints based on an inner description of the cut polytope of size k and are applied to k × k principal minors of the matrix variable of a semidefinite optimization relaxation. We propose a bilevel second order cone optimization approach to find the maximally violated k-projection polytope constraint according to a specific depth measure, and reformulate the bilevel problem as a single-level mixed binary second order cone optimization problem. We report computational results using the proposed approach within a cutting plane algorithm on instances of max-cut with 500 and 600 nodes.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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