logbook.json

{
  "schema_version": 2,
  "title": "Reproduction: Provably Data-driven Multiple Hyper-parameter Tuning with Structured Loss Function",
  "emoji": "🎯",
  "space_id": "RyeCatcher/repro-provably-data-driven-multiple-hyper-parameter-tuning-with-structured-loss-function",
  "paper": {
    "arxiv_id": "2602.02406"
  },
  "tags": [
    "icml2026-repro",
    "paper-JnuwpwbZ8D"
  ],
  "updated_at": "2026-07-28T05:18:19+00:00",
  "root": {
    "slug": "index",
    "title": "Reproduction: Provably Data-driven Multiple Hyper-parameter Tuning with Structured Loss Function",
    "file": "pages/index.md",
    "children": [
      {
        "slug": "executive-summary",
        "title": "Executive summary",
        "file": "pages/executive-summary/page.md",
        "children": []
      },
      {
        "slug": "claim-1-c1-theorem-4-1-establishes-a-general-first-order-logic-framework-giving-p",
        "title": "Claim 1: C1: Theorem 4.1 establishes a general first-order-logic framework giving p...",
        "file": "pages/claim-1-c1-theorem-4-1-establishes-a-general-first-order-logic-framework-giving-p/page.md",
        "children": []
      },
      {
        "slug": "claim-2-c2-theorem-5-1-bounds-the-pseudo-dimension-of-piecewise-polynomial-traini",
        "title": "Claim 2: C2: Theorem 5.1 bounds the pseudo-dimension of piecewise-polynomial traini...",
        "file": "pages/claim-2-c2-theorem-5-1-bounds-the-pseudo-dimension-of-piecewise-polynomial-traini/page.md",
        "children": []
      },
      {
        "slug": "claim-3-c3-theorem-6-1-extends-the-framework-to-the-bi-level-validation-loss-sett",
        "title": "Claim 3: C3: Theorem 6.1 extends the framework to the bi-level validation-loss sett...",
        "file": "pages/claim-3-c3-theorem-6-1-extends-the-framework-to-the-bi-level-validation-loss-sett/page.md",
        "children": []
      },
      {
        "slug": "claim-4-c4-theorem-7-2-shows-that-when-the-optimal-parameter-path-theta-x-alpha",
        "title": "Claim 4: C4: Theorem 7.2 shows that when the optimal parameter path theta*(x, alpha...",
        "file": "pages/claim-4-c4-theorem-7-2-shows-that-when-the-optimal-parameter-path-theta-x-alpha/page.md",
        "children": []
      },
      {
        "slug": "claim-5-c5-theorem-8-1-provides-the-first-learnability-guarantee-for-weighted-gro",
        "title": "Claim 5: C5: Theorem 8.1 provides the first learnability guarantee for weighted gro...",
        "file": "pages/claim-5-c5-theorem-8-1-provides-the-first-learnability-guarantee-for-weighted-gro/page.md",
        "children": []
      },
      {
        "slug": "claim-6-c6-theorem-8-2-derives-a-pdim-l-o-d-2-bound-for-weighted-fused-lasso",
        "title": "Claim 6: C6: Theorem 8.2 derives a Pdim(L) = O(d^2) bound for weighted fused LASSO ...",
        "file": "pages/claim-6-c6-theorem-8-2-derives-a-pdim-l-o-d-2-bound-for-weighted-fused-lasso/page.md",
        "children": []
      },
      {
        "slug": "conclusion",
        "title": "Conclusion",
        "file": "pages/conclusion/page.md",
        "children": []
      }
    ]
  },
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