| { |
| "schema_version": 1, |
| "title": "Reproduction: Finding Most Influential Sets", |
| "emoji": "🎯", |
| "space_id": "SabaPivot/repro-finding-most-influential-sets", |
| "paper": { |
| "arxiv_id": "2606.05919" |
| }, |
| "tags": [ |
| "icml2026-repro", |
| "paper-ghd0zmtpB9" |
| ], |
| "updated_at": "2026-07-19T14:54:54+00:00", |
| "root": { |
| "slug": "index", |
| "title": "Reproduction: Finding Most Influential Sets", |
| "file": "pages/index.md", |
| "children": [ |
| { |
| "slug": "executive-summary", |
| "title": "Executive summary", |
| "file": "pages/executive-summary/page.md", |
| "children": [] |
| }, |
| { |
| "slug": "claim-1-the-most-influential-sets-mis-problem-for-estimands-with-linear-fractional-leave-set-out-effects-is-reduced-to-a-one-parameter-sequence-of-top-k-selections-solved-via-dinke", |
| "title": "Claim 1: The Most Influential Sets (MIS) problem for estimands with linear-fractional leave-set-out effects is reduced to a one-parameter sequence of top-k selections solved via Dinkelbach's method (Section 3.1, Algorithm 1)", |
| "file": "pages/claim-1-the-most-influential-sets-mis-problem-for-estimands-with-linear-fractional-leave-set-out-effects-is-reduced-to-a-one-parameter-sequence-of-top-k-selections-solved-via-dinke/page.md", |
| "children": [] |
| }, |
| { |
| "slug": "claim-2-algorithm-1-costs-o-n-per-iteration-and-provably-terminates-in-at-most-m-1-ratio-updates-where-m-is-the-number-of-distinct-achievable-ratio-values-returning-a-globally-opti", |
| "title": "Claim 2: Algorithm 1 costs O(n) per iteration and provably terminates in at most M+1 ratio updates, where M is the number of distinct achievable ratio values, returning a globally optimal set (Theorem 1)", |
| "file": "pages/claim-2-algorithm-1-costs-o-n-per-iteration-and-provably-terminates-in-at-most-m-1-ratio-updates-where-m-is-the-number-of-distinct-achievable-ratio-values-returning-a-globally-opti/page.md", |
| "children": [] |
| }, |
| { |
| "slug": "claim-3-under-a-uniform-denominator-and-generated-score-stability-assumption-the-empirical-selection-objective-uniformly-approximates-the-oracle-orthogonal-score-objective-with-o-p", |
| "title": "Claim 3: Under a uniform-denominator and generated-score-stability assumption, the empirical selection objective uniformly approximates the oracle orthogonal-score objective with o_p(1) error, yielding selection consistency given a separation condition on the ratio gap (Theorem 2)", |
| "file": "pages/claim-3-under-a-uniform-denominator-and-generated-score-stability-assumption-the-empirical-selection-objective-uniformly-approximates-the-oracle-orthogonal-score-objective-with-o-p/page.md", |
| "children": [] |
| }, |
| { |
| "slug": "claim-4-at-n-10-6-and-k-10-5-the-algorithm-s-median-wall-clock-runtime-is-below-200ms-converging-in-a-median-of-three-ratio-update-iterations-section-4-1-2", |
| "title": "Claim 4: At n=10^6 and k=10^5, the algorithm's median wall-clock runtime is below 200ms, converging in a median of three ratio-update iterations (Section 4.1.2)", |
| "file": "pages/claim-4-at-n-10-6-and-k-10-5-the-algorithm-s-median-wall-clock-runtime-is-below-200ms-converging-in-a-median-of-three-ratio-update-iterations-section-4-1-2/page.md", |
| "children": [] |
| }, |
| { |
| "slug": "claim-5-a-warm-start-variant-algorithm-2-traces-the-most-influential-set-across-k-1-k-by-initializing-each-successive-top-k-problem-from-the-previous-solution-section-3-2", |
| "title": "Claim 5: A warm-start variant (Algorithm 2) traces the most influential set across k=1,...,K by initializing each successive top-k problem from the previous solution (Section 3.2)", |
| "file": "pages/claim-5-a-warm-start-variant-algorithm-2-traces-the-most-influential-set-across-k-1-k-by-initializing-each-successive-top-k-problem-from-the-previous-solution-section-3-2/page.md", |
| "children": [] |
| }, |
| { |
| "slug": "conclusion", |
| "title": "Conclusion", |
| "file": "pages/conclusion/page.md", |
| "children": [] |
| } |
| ] |
| }, |
| "agent_view_tokens": 3729, |
| "revision": "1784472894886990348" |
| } |
