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

Showing 81–90 of 423 papers

TitleStatusHype
A Game-theoretic Machine Learning Approach for Revenue Maximization in Sponsored Search—0
Application-Driven Learning: A Closed-Loop Prediction and Optimization Approach Applied to Dynamic Reserves and Demand Forecasting—0
A Fully Single Loop Algorithm for Bilevel Optimization without Hessian Inverse—0
A Penalty-Based Method for Communication-Efficient Decentralized Bilevel Programming—0
A Novel Convergence Analysis for Algorithms of the Adam Family—0
Achieving Linear Speedup in Non-IID Federated Bilevel Learning—0
Conformal Predictive Programming for Chance Constrained Optimization—0
Convergence Properties of Stochastic Hypergradients—0
An Optimization-Based Meta-Learning Model for MRI Reconstruction with Diverse Dataset—0
A Fully First-Order Method for Stochastic Bilevel Optimization—0
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Benchmark Results

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