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 226–250 of 423 papers

TitleStatusHype
Blockwise Stochastic Variance-Reduced Methods with Parallel Speedup for Multi-Block Bilevel OptimizationCode0
SimFBO: Towards Simple, Flexible and Communication-efficient Federated Bilevel Learning—0
Robust Ante-hoc Graph Explainer using Bilevel Optimization—0
One-step differentiation of iterative algorithms—0
Effective Bilevel Optimization via Minimax Reformulation—0
Balancing Test Accuracy and Security in Computerized Adaptive TestingCode0
Scalable Bilevel Optimization for Generating Maximally Representative OPF DatasetsCode0
Cooperative Lane Changing in Mixed Traffic can be Robust to Human Driver Behavior—0
Gradient scarcity with Bilevel Optimization for Graph LearningCode0
Towards Reliable Neural Machine Translation with Consistency-Aware Meta-Learning—0
Robust Pivoting Manipulation using Contact Implicit Bilevel Optimization—0
A hybrid deep-learning-metaheuristic framework for bi-level network design problemsCode0
On Momentum-Based Gradient Methods for Bilevel Optimization with Nonconvex Lower-Level—0
Implicit Bilevel Optimization: Differentiating through Bilevel Optimization Programming—0
A Lower Bound and a Near-Optimal Algorithm for Bilevel Empirical Risk Minimization—0
Communication-Efficient Federated Bilevel Optimization with Local and Global Lower Level Problems—0
Achieving Linear Speedup in Non-IID Federated Bilevel Learning—0
Communication-Efficient Federated Hypergradient Computation via Aggregated Iterative Differentiation—0
Efficient Gradient Approximation Method for Constrained Bilevel Optimization—0
A Fully First-Order Method for Stochastic Bilevel Optimization—0
Probabilistic Bilevel Coreset Selection—0
Valuing Distributed Energy Resources for Non-Wires Alternatives—0
Analyzing Inexact Hypergradients for Bilevel Learning—0
Network Utility Maximization with Unknown Utility Functions: A Distributed, Data-Driven Bilevel Optimization Approach—0
First-order penalty methods for bilevel optimization—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