SOTAVerified

Bilevel Optimization

Bilevel Optimization is a branch of optimization, which contains a nested optimization problem within the constraints of the outer optimization problem. The outer optimization task is usually referred as the upper level task, and the nested inner optimization task is referred as the lower level task. The lower level problem appears as a constraint, such that only an optimal solution to the lower level optimization problem is a possible feasible candidate to the upper level optimization problem.

Source: Efficient Evolutionary Algorithm for Single-Objective Bilevel Optimization

Papers

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Showing 351–360 of 423 papers

TitleStatusHype
Communication-Efficient Federated Bilevel Optimization with Local and Global Lower Level Problems—0
Communication-Efficient Robust Federated Learning with Noisy Labels—0
Concurrent Learning of Policy and Unknown Safety Constraints in Reinforcement Learning—0
Conformal Predictive Programming for Chance Constrained Optimization—0
Consistency analysis of bilevel data-driven learning in inverse problems—0
Contextual Stochastic Bilevel Optimization—0
Convergence and Sample Complexity of SGD in GANs—0
Convergence Properties of Stochastic Hypergradients—0
Convergent Reinforcement Learning with Function Approximation: A Bilevel Optimization Perspective—0
Convexifying Regulation Market Clearing of State-of-Charge Dependent Bid—0
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All datasetsEquilibrium-Traffic-Networks/AnaheimEquilibrium-Traffic-Networks/Eastern MassachusettsEquilibrium-Traffic-Networks/Sioux Falls

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1GIN-GAOptimality Gap0.21—Unverified
#ModelMetricClaimedVerifiedStatus
1GIN-GAOptimality Gap0.48—Unverified
#ModelMetricClaimedVerifiedStatus
1GIN-GAOptimality Gap1.44—Unverified