A new first-order method for online bilevel optimization achieves regret O(1 + V_T + H_{2,T}) over O(T log T) iterations without Hessian-vector products.
First-order penalty methods for bilevel optimization, 2024
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cs.LG 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Algorithms achieve optimal regret bounds of Ω(1+V_T) for standard bilevel local regret with O(T log T) inner gradients and Ω(T/W²) for window-averaged regret using adaptive and window-based analyses.
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Fully First-Order Algorithms for Online Bilevel Optimization
A new first-order method for online bilevel optimization achieves regret O(1 + V_T + H_{2,T}) over O(T log T) iterations without Hessian-vector products.
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Achieving Better Local Regret Bound for Online Non-Convex Bilevel Optimization
Algorithms achieve optimal regret bounds of Ω(1+V_T) for standard bilevel local regret with O(T log T) inner gradients and Ω(T/W²) for window-averaged regret using adaptive and window-based analyses.