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 231–240 of 423 papers

TitleStatusHype
Solving Bilevel Optimal Bidding Problems Using Deep Convolutional Neural Networks—0
SPABA: A Single-Loop and Probabilistic Stochastic Bilevel Algorithm Achieving Optimal Sample Complexity—0
SPARKLE: A Unified Single-Loop Primal-Dual Framework for Decentralized Bilevel Optimization—0
Spectral-Risk Safe Reinforcement Learning with Convergence Guarantees—0
SSP-GNN: Learning to Track via Bilevel Optimization—0
On Stability in Optimistic Bilevel Optimization—0
On the Convergence of Distributed Stochastic Bilevel Optimization Algorithms over a Network—0
Supervised Sparse Analysis and Synthesis Operators—0
System-Level Efficient Performance of EMLA-Driven Heavy-Duty Manipulators via Bilevel Optimization Framework with a Leader--Follower Scenario—0
Targeted Unlearning Using Perturbed Sign Gradient Methods With Applications On Medical Images—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