| { |
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| "title": "Reproduction: Optimal structure learning and conditional independence testing", |
| "emoji": "🎯", |
| "space_id": "rcgp/repro-optimal-structure-learning-and-conditional-independence-testing", |
| "paper": null, |
| "tags": [ |
| "icml2026-repro", |
| "paper-21061" |
| ], |
| "updated_at": "2026-07-23T14:08:13+00:00", |
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| "title": "Reproduction: Optimal structure learning and conditional independence testing", |
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| { |
| "slug": "executive-summary", |
| "title": "Executive Summary", |
| "file": "pages/executive-summary/page.md", |
| "children": [] |
| }, |
| { |
| "slug": "claim-1-theorem-3-1-ci-testing-and-structure-learning-connection", |
| "title": "Claim 1: Theorem 3.1 - CI Testing and Structure Learning Connection", |
| "file": "pages/claim-1-theorem-3-1-ci-testing-and-structure-learning-connection/page.md", |
| "children": [] |
| }, |
| { |
| "slug": "claim-2-theorem-4-1-4-2-bernoulli-and-gaussian-models", |
| "title": "Claim 2: Theorem 4.1/4.2 - Bernoulli and Gaussian Models", |
| "file": "pages/claim-2-theorem-4-1-4-2-bernoulli-and-gaussian-models/page.md", |
| "children": [] |
| }, |
| { |
| "slug": "claim-3-theorem-5-1-nonparametric-models", |
| "title": "Claim 3: Theorem 5.1 - Nonparametric Models", |
| "file": "pages/claim-3-theorem-5-1-nonparametric-models/page.md", |
| "children": [] |
| }, |
| { |
| "slug": "claim-4-algorithm-1-pc-tree-algorithm-efficiency", |
| "title": "Claim 4: Algorithm 1 - PC-tree Algorithm Efficiency", |
| "file": "pages/claim-4-algorithm-1-pc-tree-algorithm-efficiency/page.md", |
| "children": [] |
| }, |
| { |
| "slug": "conclusion", |
| "title": "Conclusion", |
| "file": "pages/conclusion/page.md", |
| "children": [] |
| } |
| ] |
| }, |
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