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 301–310 of 423 papers

TitleStatusHype
Learning Surrogate Losses—0
Learning Theory for Kernel Bilevel Optimization—0
Learning to Defend by Learning to Attack—0
Learning to Generalize to Unseen Tasks with Bilevel Optimization—0
Learning to Learn Semantic Factors in Heterogeneous Image Classification—0
Learning to Rank for Active Learning via Multi-Task Bilevel Optimization—0
Learning to Re-weight Examples with Optimal Transport for Imbalanced Classification—0
Learning Variational Models with Unrolling and Bilevel Optimization—0
Learning with Limited Samples -- Meta-Learning and Applications to Communication Systems—0
Learn to Bid as a Price-Maker Wind Power Producer—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