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 291–300 of 423 papers

TitleStatusHype
Joint Differentiable Optimization and Verification for Certified Reinforcement Learning—0
Joint Perceptual Learning for Enhancement and Object Detection in Underwater Scenarios—0
Joint Unsupervised and Supervised Training for Automatic Speech Recognition via Bilevel Optimization—0
Learning to Generate Image Source-Agnostic Universal Adversarial Perturbations—0
Learning Implicit Generative Models by Teaching Explicit Ones—0
Learning Regularization Parameters of Inverse Problems via Deep Neural Networks—0
Learning Sample Reweighting for Accuracy and Adversarial Robustness—0
Learning Sample Reweighting for Adversarial Robustness—0
Learning Sparsity-Promoting Regularizers using Bilevel Optimization—0
Learning sparsity-promoting regularizers for linear inverse problems—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