{
 "schema_version": 1,
 "title": "Repro: Optimal Regularization for Performative Learning",
 "emoji": "chart",
 "space_id": "snaykey/repro-optimal-reg-performative",
 "paper": {
  "openreview_id": "G4ve69pimc"
 },
 "tags": [
  "icml2026-repro",
  "paper-G4ve69pimc"
 ],
 "updated_at": "2026-07-27T00:00:00+00:00",
 "root": {
  "slug": "index",
  "title": "Repro: Optimal Regularization for Performative Learning",
  "file": "pages/index.md",
  "children": [
   {
    "slug": "executive-summary",
    "title": "Executive summary",
    "file": "pages/executive-summary/page.md",
    "children": []
   },
   {
    "slug": "claim-1-population-excess-risk-characterization",
    "title": "In the population setting, Theorem 1 characterizes excess risk as a function of the magnitude and direction of the performative effect together with spurious features (Section 4, Theorem 1).",
    "file": "pages/claim-1-population-excess-risk-characterization/page.md",
    "children": []
   },
   {
    "slug": "claim-2-optimal-regularization-proportional",
    "title": "Corollary 2 shows the optimal regularization parameter in the population regime is proportional to the strength of the performative effect, with optimal risk remaining strictly positive (Section 4, Corollary 2).",
    "file": "pages/claim-2-optimal-regularization-proportional/page.md",
    "children": []
   },
   {
    "slug": "claim-3-deterministic-equivalent-fixed-point",
    "title": "Theorem 3 establishes a deterministic equivalent of the performative fixed point for over-parameterized ridge regression when the number of features exceeds the number of samples (Section 5, Theorem 3).",
    "file": "pages/claim-3-deterministic-equivalent-fixed-point/page.md",
    "children": []
   },
   {
    "slug": "claim-4-optimal-regularization-sign-flip-noise",
    "title": "Theorem 4 shows the optimal regularization moves in the same direction as the performative effect on predictive features under low noise, but in the opposite direction under high noise, in the over-parameterized regime (Section 5, Theorem 4).",
    "file": "pages/claim-4-optimal-regularization-sign-flip-noise/page.md",
    "children": []
   },
   {
    "slug": "claim-5-overparam-performativity-improves-risk",
    "title": "Numerical experiments in Section 6 confirm that in the over-parameterized setting, performative effects can improve optimally-regularized risk when performativity reinforces existing trends, contrasting with the population-regime degradation (Section 6).",
    "file": "pages/claim-5-overparam-performativity-improves-risk/page.md",
    "children": []
   },
   {
    "slug": "conclusion",
    "title": "Conclusion",
    "file": "pages/conclusion/page.md",
    "children": []
   }
  ]
 }
}