| { |
| "schema_version": 1, |
| "title": "Repro - Learning-Augmented Online Covering Problems", |
| "emoji": "馃幆", |
| "space_id": "rdubwiley/learning-augmented-online-covering-problems-repro", |
| "paper": { |
| "arxiv_id": "2507.06032" |
| }, |
| "tags": [ |
| "icml2026-repro", |
| "paper-vbty65Z76C" |
| ], |
| "updated_at": "2026-07-18T02:23:11+00:00", |
| "root": { |
| "slug": "index", |
| "title": "Repro - Learning-Augmented Online Covering Problems", |
| "file": "pages/index.md", |
| "children": [ |
| { |
| "slug": "claim-1-framework-converts-online-algorithm-with-competitive-ratio-k-into-one-with-where-is-prediction-error", |
| "title": "Claim 1: Framework converts online algorithm with competitive ratio 蟻(k,路) into one with 蟻(畏,路) where 畏 is prediction error", |
| "file": "pages/claim-1-framework-converts-online-algorithm-with-competitive-ratio-k-into-one-with-where-is-prediction-error/page.md", |
| "children": [] |
| }, |
| { |
| "slug": "claim-2-with-accurate-enough-prediction-resulting-competitive-ratio-breaks-through-worst-case-online-lower-bounds", |
| "title": "Claim 2: With accurate enough prediction, resulting competitive ratio breaks through worst-case online lower bounds", |
| "file": "pages/claim-2-with-accurate-enough-prediction-resulting-competitive-ratio-breaks-through-worst-case-online-lower-bounds/page.md", |
| "children": [] |
| }, |
| { |
| "slug": "claim-3-degrades-smoothly-as-prediction-error-grows-applies-to-facility-location-steiner-problems-set-cover", |
| "title": "Claim 3: Degrades smoothly as prediction error grows, applies to facility location, Steiner problems, set cover", |
| "file": "pages/claim-3-degrades-smoothly-as-prediction-error-grows-applies-to-facility-location-steiner-problems-set-cover/page.md", |
| "children": [] |
| }, |
| { |
| "slug": "conclusion", |
| "title": "Conclusion", |
| "file": "pages/conclusion/page.md", |
| "children": [] |
| } |
| ] |
| }, |
| "agent_view_tokens": 4896, |
| "revision": "1784341391595631695" |
| } |