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Record W4404697950 · doi:10.23952/jnva.5.2021.5.13

Inertial-type projection methods for solving convex constrained monotone nonlinear equations with applications to robotic motion control

2021· article· en· W4404697950 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 · 2021
Typearticle
Languageen
FieldComputer Science
TopicOptimization and Variational Analysis
Canadian institutionsnot available
FundersPetroleum Technology Development FundDeutscher Akademischer Austauschdienst
KeywordsMonotone polygonRegular polygonType (biology)Nonlinear systemProjection (relational algebra)Projection methodInertial frame of referenceMathematicsMotion (physics)Control theory (sociology)Computer scienceMathematical optimizationControl (management)Dykstra's projection algorithmArtificial intelligenceAlgorithmPhysicsGeometryClassical mechanics

Abstract

fetched live from OpenAlex

In this paper, we introduce two derivative-free projection iterative algorithms for solving a system of nonlinear monotone operator equations.The two proposed algorithms can be viewed as twostep methods where the first step uses an inertial effect in every iteration.The global convergence of the proposed algorithms is established under some mild assumptions.We present numerical experiments to show the efficiency and advantage of the inertial projection steps of the proposed algorithms and compare it with some existing methods for solving nonlinear problems.Finally, we consider the problem of solving a motion control problem involving a two-joint planar robotic manipulator.

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 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 score0.100
Threshold uncertainty score0.534

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.024
GPT teacher head0.330
Teacher spread0.305 · 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