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Record W4402137846 · doi:10.21105/jcon.00161

JSOSuite.jl: Solving continuous optimization problems with JuliaSmoothOptimizers

2024· article· en· W4402137846 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJuliaCon Proceedings · 2024
Typearticle
Languageen
FieldMathematics
TopicAdvanced Optimization Algorithms Research
Canadian institutionsPolytechnique MontréalGroup for Research in Decision AnalysisHEC Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSolverCover (algebra)Problem solverComputer scienceMathematical optimizationOptimization problemInterface (matter)Continuous optimizationNonlinear systemNonlinear programmingAlgorithmMathematicsProgramming languageComputational scienceParallel computingEngineeringMulti-swarm optimization

Abstract

fetched live from OpenAlex

JSOSuite.jl is a new Julia package offering a user-friendly interface for continuous nonlinear optimization.The solvers available cover unconstrained to generally-constrained, and least-squares problems.This new package caters to practitioners as it does not require an understanding of the inner mechanism of solvers, but instead performs a cursory analysis of the problem to match it with an appropriate solver.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.430
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.029
GPT teacher head0.311
Teacher spread0.282 · 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