| { | |
| "schema_version": 2, | |
| "title": "Reproduction: FAB: A First-Order AB-based Gradient Algorithm for Distributed Bilevel Optimization over Time-Varying Directed Graphs", | |
| "emoji": "🎯", | |
| "space_id": "algorise/repro-fab-a-first-order-ab-based-gradient-algorithm-for-distributed-bilevel-optimization-over-ti", | |
| "paper": { | |
| "arxiv_id": "2605.06328" | |
| }, | |
| "tags": [ | |
| "icml2026-repro", | |
| "paper-coINrhVRkL" | |
| ], | |
| "updated_at": "2026-07-22T13:17:37+00:00", | |
| "root": { | |
| "slug": "index", | |
| "title": "Reproduction: FAB: A First-Order AB-based Gradient Algorithm for Distributed Bilevel Optimization over Time-Varying Directed Graphs", | |
| "file": "pages/index.md", | |
| "children": [ | |
| { | |
| "slug": "executive-summary", | |
| "title": "Executive summary", | |
| "file": "pages/executive-summary/page.md", | |
| "children": [] | |
| }, | |
| { | |
| "slug": "claim-1-fab-combines-push-pull-gradient-tracking-with-a-value-function-penalty-reformulation-for-distributed-bilevel-optimization-sec-2-1-algorithm-1", | |
| "title": "Claim 1: FAB combines Push-Pull gradient tracking with a value-function penalty reformulation for distributed bilevel optimization (Sec 2.1, Algorithm 1)", | |
| "file": "pages/claim-1-fab-combines-push-pull-gradient-tracking-with-a-value-function-penalty-reformulation-for-distributed-bilevel-optimization-sec-2-1-algorithm-1/page.md", | |
| "children": [] | |
| }, | |
| { | |
| "slug": "claim-2-theorem-3-4-fab-converges-at-rate-o-k-2-3-in-hypergradient-norm-for-nonconvex-strongly-convex-bilevel-problems-sec-3-thm-3-4", | |
| "title": "Claim 2: Theorem 3.4: FAB converges at rate O(K^-2/3) in hypergradient norm for nonconvex-strongly-convex bilevel problems (Sec 3, Thm 3.4)", | |
| "file": "pages/claim-2-theorem-3-4-fab-converges-at-rate-o-k-2-3-in-hypergradient-norm-for-nonconvex-strongly-convex-bilevel-problems-sec-3-thm-3-4/page.md", | |
| "children": [] | |
| }, | |
| { | |
| "slug": "claim-3-theorem-3-6-push-pull-gradient-tracking-over-time-varying-digraphs-achieves-o-k-1-rate-for-single-level-nonconvex-optimization-sec-3-thm-3-6", | |
| "title": "Claim 3: Theorem 3.6: Push-Pull gradient tracking over time-varying digraphs achieves O(K^-1) rate for single-level nonconvex optimization (Sec 3, Thm 3.6)", | |
| "file": "pages/claim-3-theorem-3-6-push-pull-gradient-tracking-over-time-varying-digraphs-achieves-o-k-1-rate-for-single-level-nonconvex-optimization-sec-3-thm-3-6/page.md", | |
| "children": [] | |
| }, | |
| { | |
| "slug": "claim-4-proposition-3-5-consensus-error-of-decision-tracking-and-auxiliary-variables-bounded-at-o-k-1-under-time-varying-digraphs-sec-3-prop-3-5", | |
| "title": "Claim 4: Proposition 3.5: consensus error of decision, tracking, and auxiliary variables bounded at O(K^-1) under time-varying digraphs (Sec 3, Prop 3.5)", | |
| "file": "pages/claim-4-proposition-3-5-consensus-error-of-decision-tracking-and-auxiliary-variables-bounded-at-o-k-1-under-time-varying-digraphs-sec-3-prop-3-5/page.md", | |
| "children": [] | |
| }, | |
| { | |
| "slug": "claim-5-fab-validated-on-distributed-hyperparameter-tuning-fashion-mnist-hyper-cleaning-bert-imdb-and-rl-policy-evaluation-sec-4-1-4-3-fig-1-8", | |
| "title": "Claim 5: FAB validated on distributed hyperparameter tuning, Fashion-MNIST hyper-cleaning, BERT/IMDB, and RL policy evaluation (Sec 4.1-4.3, Fig 1-8)", | |
| "file": "pages/claim-5-fab-validated-on-distributed-hyperparameter-tuning-fashion-mnist-hyper-cleaning-bert-imdb-and-rl-policy-evaluation-sec-4-1-4-3-fig-1-8/page.md", | |
| "children": [] | |
| }, | |
| { | |
| "slug": "conclusion", | |
| "title": "Conclusion", | |
| "file": "pages/conclusion/page.md", | |
| "children": [] | |
| } | |
| ] | |
| }, | |
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