backup: 2026-08-29 06:59
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#+title: thesis/todos
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#+filetags: :project: :todo:
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* Writing — chapters
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* TODO Write Ch. 1 (Introduction)
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- Hook: imbalance + noise are everywhere, standard losses fail silently
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- Gap: no existing method does AUC optimization + noise robustness together
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- ROLL's claim: distributional objective, robustness as structural consequence
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- Close with chapter roadmap
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* TODO Write Ch. 5 (Discussion)
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- Explain WHY ROLL-AOC is noise robust (KDE distributional fit vs isolated gradients)
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- Explain WHY Bank Marketing fails (open question, speculate honestly)
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- Explain WHY GCE/MAE fail under asymmetric imbalanced noise
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- Compare mechanism with LibAUC (same objective, different path)
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* TODO Write Ch. 6 (Conclusion)
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- Summary: differentiable AUC surrogate via score-distribution fitting
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- Key result: noise robustness validated on KEEL (5/10/20%) and CIFAR-10N (≤40%)
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- Limitations: Bank Marketing, 99-pass cost, bandwidth scheduler hyperparameter
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- Future work: learned bandwidth, partial-AUC variant, multi-class extension
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* TODO Finish Ch. 4 (Results) — remaining stubs
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- Write Summary section (sec:experiments:summary) — key points noted in comments
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- Decide: write or drop Ablation Study and Sensitivity Analysis sections
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- Fill all \cite{TODO} placeholders in experiments.tex
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* TODO Review Ch. 4 (Results) end-to-end
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- Check narrative flow after noise section was added
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- Confirm KEEL/CIFAR-10N/large-dataset table interpretations are accurate
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- Verify roll-tpr90 is correctly described as secondary/special-case throughout
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* Writing — front/back matter
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* TODO Write English abstract
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* TODO Write Hebrew abstract
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* TODO Fill Acknowledgements (Main_pages/acknowledgements.tex)
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* Writing — Ch. 2 & 3 loose ends
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* TODO Verify alpha notation w.r.t. FPR — eq:fpr-cdf writes FPR(τ) = F̂₀(τ) and threshold as τ = F̂₀⁻¹(α), but standard FPR = P(score > τ | y=0) = 1−F₀(τ) requires τ = F̂₀⁻¹(1−α). Check for sign/notation inconsistency throughout method.tex and appendix_gauss_grad.tex.
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* TODO Add graphs of CDF tracking for gaussian, KDE, roll.
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* TODO Cite in sec:related-work (Ch. 2):
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- Benchmarking Deep AUROC Optimization (arXiv 2203.14177) — cite in 2.2 as survey of AUROC losses; finding: composite losses best overall, barrier hinge best under noise
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- LibAUC pAUCLoss / SOPAs (arXiv 2203.01505) — cite in 2.3 as partial AUC baseline
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- "Closing the Approximation Gap" (arXiv 2512.01213, Dec 2025) — cite in 2.3 as recent concurrent work on partial AUC
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- "When AUC meets DRO" — cite in 2.3 as DRO-based partial AUC approach
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* Experiments — open questions
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* TODO Debug banking dataset — results unexpectedly low (roll-aoc 0.511 vs GCE 0.746), investigate root cause
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* TODO Check if LibAUC pAUCLoss (one-way partial AUC / SOPAs) should be added as baseline
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- Already have LibAUC as dependency; low-cost to add
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- Most direct competitor to roll-tpr90 (both target a fixed FPR region)
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- See: https://docs.libauc.org/examples/pauc.html
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* Final pass
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* TODO Build full PDF and proofread end-to-end
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* TODO Check all cross-references (\Cref, \label) are consistent after restructuring
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* TODO Verify Hebrew ToC entries match English section titles
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* DONE [#A] Rerun keel noised experiments — data exists in results-final/keel-noise-05/10/20
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* DONE Restructure thesis per mentor guidelines (2026-08-17)
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- [x] Focus framing on noise resistance + AUC solution (primary story)
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- [x] Minimize single-point optimization coverage (brief mention only)
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- [x] Ch. 2 restructured: ROC/AUC → Noisy Labels → KDE → Imbalanced → NP
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- [x] Ch. 3 restructured: AUC as primary objective, ROLL-AOC promoted
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- [x] Noise results table added to Ch. 4
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