MétaCan
Menu
Back to cohort
Record W1972168423 · doi:10.3934/jimo.2008.4.125

Canonical dual approach to solving 0-1 quadratic programming problems

2008· article· en· W1972168423 on OpenAlexaff
Shu‐Cherng Fang, David Yang Gao, Ruey-Lin Sheu, Soon‐Yi Wu

Bibliographic record

VenueJournal of Industrial and Management Optimization · 2008
Typearticle
Languageen
FieldComputer Science
TopicOptimization and Variational Analysis
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsDual polyhedronDuality gapDual (grammatical number)Duality (order theory)ConvexityMathematicsCanonical transformationQuadratic programmingConvex analysisStrong dualityCanonical formMathematical optimizationWolfe dualityPerturbation functionMinificationLinear programmingTransformation (genetics)Convex optimizationRegular polygonWeak dualityOptimization problemCombinatoricsPure mathematics

Abstract

fetched live from OpenAlex

By using the canonical dual transformation developedrecently, we derive a pair of canonical dual problems for 0-1quadratic programming problems in both minimization and maximizationform. Regardless convexity, when the canonical duals are solvable,no duality gap exists between the primal and corresponding dualproblems. Both global and local optimality conditions are given. Analgorithm is presented for finding global minimizers, even when theprimal objective function is not convex. Examples are included toillustrate this new approach.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.053
GPT teacher head0.237
Teacher spread0.185 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations66
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Industrial and Management OptimizationSame topicOptimization and Variational AnalysisFrench-language works237,207