logbook.json

{
  "schema_version": 2,
  "title": "Reproduction: Provably Data-driven Lagrangian Relaxation for Mixed Integer Linear Programming",
  "emoji": "🎯",
  "space_id": "RyeCatcher/repro-provably-data-driven-lagrangian-relaxation-for-mixed-integer-linear-programming",
  "paper": {
    "arxiv_id": "2605.19052"
  },
  "tags": [
    "icml2026-repro",
    "paper-OwLuqetJuB"
  ],
  "updated_at": "2026-07-28T05:18:17+00:00",
  "root": {
    "slug": "index",
    "title": "Reproduction: Provably Data-driven Lagrangian Relaxation for Mixed Integer Linear Programming",
    "file": "pages/index.md",
    "children": [
      {
        "slug": "executive-summary",
        "title": "Executive summary",
        "file": "pages/executive-summary/page.md",
        "children": []
      },
      {
        "slug": "claim-1-c1-for-learned-lagrangian-relaxation-multipliers-over-s-coupling-constrai",
        "title": "Claim 1: C1: For learned Lagrangian Relaxation multipliers over s coupling constrai...",
        "file": "pages/claim-1-c1-for-learned-lagrangian-relaxation-multipliers-over-s-coupling-constrai/page.md",
        "children": []
      },
      {
        "slug": "claim-2-c2-a-minimax-lower-bound-of-s-n-is-proven-showing-linear-dependence",
        "title": "Claim 2: C2: A minimax lower bound of Ω(s/√N) is proven, showing linear dependence ...",
        "file": "pages/claim-2-c2-a-minimax-lower-bound-of-s-n-is-proven-showing-linear-dependence/page.md",
        "children": []
      },
      {
        "slug": "claim-3-c3-stochastic-gradient-ascent-with-iterate-averaging-is-shown-to-achieve",
        "title": "Claim 3: C3: Stochastic Gradient Ascent with iterate averaging is shown to achieve ...",
        "file": "pages/claim-3-c3-stochastic-gradient-ascent-with-iterate-averaging-is-shown-to-achieve/page.md",
        "children": []
      },
      {
        "slug": "claim-4-c4-the-framework-is-extended-to-learning-to-warm-start-sub-gradient-ascen",
        "title": "Claim 4: C4: The framework is extended to learning-to-warm-start sub-gradient ascen...",
        "file": "pages/claim-4-c4-the-framework-is-extended-to-learning-to-warm-start-sub-gradient-ascen/page.md",
        "children": []
      },
      {
        "slug": "claim-5-c5-the-covering-number-of-the-dual-multiplier-class-u-is-bounded-as-log-n",
        "title": "Claim 5: C5: The covering number of the dual multiplier class U is bounded as log N...",
        "file": "pages/claim-5-c5-the-covering-number-of-the-dual-multiplier-class-u-is-bounded-as-log-n/page.md",
        "children": []
      },
      {
        "slug": "claim-6-c6-the-dual-function-u-p-is-shown-to-be-concave-in-with-subgradient",
        "title": "Claim 6: C6: The dual function u(π,P) is shown to be concave in π with subgradient ...",
        "file": "pages/claim-6-c6-the-dual-function-u-p-is-shown-to-be-concave-in-with-subgradient/page.md",
        "children": []
      },
      {
        "slug": "conclusion",
        "title": "Conclusion",
        "file": "pages/conclusion/page.md",
        "children": []
      }
    ]
  },
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