logbook.json

{
  "schema_version": 1,
  "title": "Reproduction: A Linearly Convergent Proximal Subgradient Algorithm for Sparse Portfolio Optimization with Transaction Cost",
  "emoji": "🎯",
  "space_id": "Umong/repro-a-linearly-convergent-proximal-subgradient-algorithm-for-sparse-portfolio-optimization-wit",
  "paper": null,
  "tags": [
    "icml2026-repro",
    "paper-yZAo4TPqhE"
  ],
  "updated_at": "2026-07-18T19:19:55+00:00",
  "root": {
    "slug": "index",
    "title": "Reproduction: A Linearly Convergent Proximal Subgradient Algorithm for Sparse Portfolio Optimization with Transaction Cost",
    "file": "pages/index.md",
    "children": [
      {
        "slug": "executive-summary",
        "title": "Executive summary",
        "file": "pages/executive-summary/page.md",
        "children": []
      },
      {
        "slug": "claim-1-establish-r-linear-convergence-rate-of-proximal-subgradient-algorithm-psga-by-showing-kurdyka-ojasiewicz-exponent-is-1-2",
        "title": "Claim 1: Establish R-linear convergence rate of proximal subgradient algorithm (PSGA) by showing Kurdyka-Łojasiewicz exponent is 1/2.",
        "file": "pages/claim-1-establish-r-linear-convergence-rate-of-proximal-subgradient-algorithm-psga-by-showing-kurdyka-ojasiewicz-exponent-is-1-2/page.md",
        "children": []
      },
      {
        "slug": "claim-2-achieve-lower-risk-while-keeping-higher-return-than-classical-transaction-cost-optimization-models-on-real-market-data",
        "title": "Claim 2: Achieve lower risk while keeping higher return than classical transaction cost optimization models on real-market data.",
        "file": "pages/claim-2-achieve-lower-risk-while-keeping-higher-return-than-classical-transaction-cost-optimization-models-on-real-market-data/page.md",
        "children": []
      },
      {
        "slug": "conclusion",
        "title": "Conclusion",
        "file": "pages/conclusion/page.md",
        "children": []
      }
    ]
  },
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  "revision": "1784402395286541590"
}