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Record W4393621040 · doi:10.23952/jnva.8.2024.3.04

A Bregman projection algorithm with self adaptive step sizes for split variational inequality problems involving non-Lipschitz operators

2024· article· en· W4393621040 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Nonlinear and Variational Analysis · 2024
Typearticle
Languageen
FieldComputer Science
TopicOptimization and Variational Analysis
Canadian institutionsnot available
FundersCentre Scientifique et Technique du BâtimentFundamental Research Funds for the Central UniversitiesNatural Science Foundation of ChongqingNational Natural Science Foundation of China
KeywordsVariational inequalityLipschitz continuityProjection (relational algebra)MathematicsBregman divergenceInequalityAlgorithmApplied mathematicsMathematical optimizationComputer scienceMathematical analysis

Abstract

fetched live from OpenAlex

The purpose of this paper is to investigate a Bregman projection algorithm for solving the split variational inequality problem governed by pseudomonotone and not necessarily Lipschitz continuous operators in real Hilbert spaces.The proposed algorithm is motivated by the ideas of the Halpern method, the CQ method, and Tseng's extragradient method.The step size sequences are determined by employing Armijo line search techniques.The strong convergence theorem is established without the prior knowledge of the operator norm and the Lipschitz continuous assumption on the operators involved.Some numerical experiments with graphical illustrations are presented to demonstrate the effectiveness and the performance of our proposed algorithm in comparison with some existing ones.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.471
Threshold uncertainty score0.693

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.015
GPT teacher head0.260
Teacher spread0.244 · 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