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{
"schema_version": 1,
"title": "Repro - Near-Optimal and Efficient First-Order Algorithm for Multi-Task Learning with Shared Linear Representation",
"emoji": "🎯",
"space_id": "rdubwiley/near-optimal-and-efficient-first-order-algorithm-repro",
"paper": {
"arxiv_id": "2605.00473"
},
"tags": [
"icml2026-repro",
"paper-TnquAvyTtL"
],
"updated_at": "2026-07-19T02:53:04+00:00",
"root": {
"slug": "index",
"title": "Repro - Near-Optimal and Efficient First-Order Algorithm for Multi-Task Learning with Shared Linear Representation",
"file": "pages/index.md",
"children": [
{
"slug": "claim-1-first-order-algorithm-for-multi-task-learning-with-shared-linear-representation-converges-in-1-iterations",
"title": "Claim 1: First-order algorithm for multi-task learning with shared linear representation converges in Õ(1) iterations",
"file": "pages/claim-1-first-order-algorithm-for-multi-task-learning-with-shared-linear-representation-converges-in-1-iterations/page.md",
"children": []
},
{
"slug": "claim-2-achieves-near-optimal-estimation-error-of-dk-tn-improving-over-existing-methods-by-factor-k",
"title": "Claim 2: Achieves near-optimal estimation error of Õ(dk/(TN)) improving over existing methods by factor k",
"file": "pages/claim-2-achieves-near-optimal-estimation-error-of-dk-tn-improving-over-existing-methods-by-factor-k/page.md",
"children": []
},
{
"slug": "claim-3-guarantees-computational-efficiency-for-jointly-learning-shared-representation-and-task-specific-parameters",
"title": "Claim 3: Guarantees computational efficiency for jointly learning shared representation and task-specific parameters",
"file": "pages/claim-3-guarantees-computational-efficiency-for-jointly-learning-shared-representation-and-task-specific-parameters/page.md",
"children": []
},
{
"slug": "conclusion",
"title": "Conclusion",
"file": "pages/conclusion/page.md",
"children": []
}
]
},
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