Writing study: Robust Contextual Optimization with Missing Covariates
← ICML 2026 oral writing corpus
Qingyuan Xu, Ruiwei Jiang · Official ICML 2026 oral record
Figure, table and section ledger
Editorial contribution type: Theory & formal analysis (primary).
Layout extraction, not a required paper template. Counts are distinct caption labels; a multi-panel figure counts once. Section spans are estimated from heading positions, including floats and whitespace. Method and limitations.
- Canonical PDF
- 62 physical pages
- Before references / appendix
- ≈ 9.16 page-equivalents
- Main figures / tables
- 6 / 2
- Attached appendix figures / tables
- 3 / 5
- Attached appendix span
- ≈ 50.91 page-equivalents
Section-by-section lengths and source pages
The title/abstract/front matter precede the first numbered heading. A span ends at the next detected top-level heading, not at the last sentence; end-page whitespace is included. References and statements are listed separately. These are not measurements of text-only or artwork area.
| Top-level heading | Starts on PDF page | Estimated span | Share of entire PDF |
|---|---|---|---|
| 1. Introduction | 1 | ≈ 1.08 pp. | 1.74% |
| 2. A Unified Model | 2 | ≈ 1.74 pp. | 2.81% |
| 3. Tractable Reformulations and Statistical | 4 | ≈ 3.93 pp. | 6.34% |
| 4. Numerical Experiments | 8 | ≈ 1.96 pp. | 3.16% |
| Impact Statement | 10 | ≈ 0.08 pp. | 0.13% |
| Acknowledgements | 10 | ≈ 0.05 pp. | 0.08% |
| References | 10 | ≈ 1.92 pp. | 3.1% |
| A. Notations | 12 | ≈ 1 pp. | 1.61% |
| B. Additional Literature Review | 13 | ≈ 2 pp. | 3.23% |
| C. Technical Proofs | 15 | ≈ 35 pp. | 56.45% |
| D. Additional Results | 50 | ≈ 6.49 pp. | 10.47% |
| E. Experimental Details | 56 | ≈ 6.43 pp. | 10.37% |
All detected figure and table locations
Main text
Argument and organization
- 1 Introduction; 2 A Unified Model
Defines a decision problem, positivity/MAR assumptions and observed-data-consistent ambiguity sets.
- 3 Tractable Reformulations and Statistical Guarantees
Separates discrete and continuous outcomes, with distinct reformulation and guarantee subsections.
- 4 Numerical Experiments
Tests scaling, radius effects, overall comparisons and controlled sensitivity in a contextual newsvendor problem.
Problem, claim and contribution
Missingness is tied to decision loss rather than reconstruction accuracy, and the introduction explains why imputing a dataset need not calibrate downstream decision uncertainty.
Sections 1–2, physical pp.1–3 · Main paper
Argument and section order
Reliability, statistical efficiency and tractability are announced as separate goals and then addressed by distinct propositions and numerical checks.
Section 2 continuation and Section 3, pp.4–7 · Main paper
Figures, captions and visual explanation
Separate runtime tables vary raw sample size versus latent-support size; separate cost/reliability panels expose the conservatism trade-off and sensitivity axes.
Tables 1–2 and Figure 2, p.8; Figures 3–6, p.9 · Main paper
Tables, comparisons and evidence
The experiments use 100 replications and distinguish 20–80% quantile bands from standard-deviation bands. Radius selection and test-information oracle diagnostics are explicitly separated in the appendix.
Section 4, pp.8–9; Appendix E.4–E.6, pp.58–59 · Main paper
Appendix and reproducibility
Baseline definitions, the candidate radius grid, deployable holdout selection and a diagnostic-only oracle are specified separately from mathematical proofs.
Appendices C–E; selected E.3–E.6, pp.58–59 · Main paper
Clarity and writing conventions
The main theory names complete-case positivity and MAR; it explains that unrestricted MNAR requires additional assumptions or external information.
Assumptions 2.4–2.5 and surrounding discussion, p.3 · Main paper
What to reuse—and what not to infer
Transferable lesson: Organize robust decision methods around assumptions, tractability and statistical guarantees, then evaluate decision quality and conservatism separately.
Boundary: The guarantees are conditional on positivity, MAR and further regularity; they do not cover unrestricted missing-not-at-random data. Empirical reliability compares realized cost with a validation estimate in Appendix E.5 and should not be equated automatically with theorem coverage. Figure 4’s caption says up to10,000 samples while its plotted labels and appendix table end at5,994.
Apply this lesson using the argument and evidence worksheet.
Inspection record and sources
- Checked
- 2026-10-07
- Reading status
- Writing-focused manuscript scan + selected visuals inspected
- Main text
- Writing-focused scan across physical PDF pp.1–9, covering framing, section progression, definitions, method/evidence explanations, captions and scope. Physical pages extracted individually to avoid form-feed pagination errors. Selected full-page rasters inspected; not exhaustive line-by-line technical verification or experimental reproduction.
- Appendix / supplement
- Reference/impact boundary p.10 and appendix heading inventory A–E checked. Selected detailed reading of baselines, holdout/oracle tuning and reliability definitions E.3–E.6 (pp.58–59). Long proofs, continuous-covariate extensions and all experimental cases were not independently verified.
- Visually inspected PDF pages
- 8, 9
This is a writing-focused scan of the manuscript and the stated supplementary scope: framing, organization, visual explanation, evidence presentation and wording. It is not a line-by-line proof audit, reproduction of results or exhaustive scientific review.