“International Conference on Variational Analysis and Nonsmooth Optimization” In honor of the 65th birthday of Christiane Tammer (Martin Luther University Halle-Wittenberg)
Bibliographic record
Abstract
This special issue covers the "International Conference on Variational Analysis and Nonsmooth Optimization," held online on July 15 -July 16, 2021.The mission of the conference was to bring together recognized experts as well as early-career researchers from countries across the globe to exchange the latest insights and present the recent scientific findings related to nonlinear and variational analysis, nonsmooth, vector, and set optimization, control theory, operations research, and related disciplines.A wealth of applications in economics, management science, engineering, mechanics, and behavioral sciences has led to the emergence of these theories.As a result of these important applications, these topics represent thriving research areas and branches of applied mathematics that continue to expand.This conference explored new developments, fostered new ideas, and encouraged participants' collaborations to generate new knowledge that can be applied to existing problems and future applications.Details on the conference, along with a brief description of the remarkable accomplishments of Professor Christiane Tammer, including laudations and conference photographs, can be found here: https://wiki.math.ntnu.no/_media/icvano2021/icvano_2021_booklet.pdfThis special issue is comprised of eleven articles whose contributions are as follows.The paper "A unified approach to Bishop-Phelps and scalarizing functionals" by J. Jahn is devoted to a thorough and unifying investigation of newly proposed and existing scalarizing functionals associated with certain ordering cones.The proposed notion subsumes many such functionals, including the celebrated Bishop-Phelps functionals.It is shown that the studied scalarizing functionals provide a convenient framework for exploring fixed and variable order structures.The key advantages of the proposed approach are illustrated by means of numerous examples.Interesting applications to vector optimization and set optimization are also supplied.The objective of B. Mordukhovich, and O. Nguyen in the paper "Subdifferential Calculus for Ordered Multifunctions with Applications to Set-Valued Optimization" is to study subdifferentials for set-valued maps taking values in certain ordered spaces.Two subdifferentials, basic and singular, are introduced, and new calculus rules are established.The calculus rules
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.021 | 0.009 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".