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 201–225 of 423 papers

TitleStatusHype
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
Boosting Differentiable Causal Discovery via Adaptive Sample ReweightingCode1
Implicit Bilevel Optimization: Differentiating through Bilevel Optimization Programming—0
Nystrom Method for Accurate and Scalable Implicit DifferentiationCode1
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
On Penalty-based Bilevel Gradient Descent MethodCode1
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
First-order penalty methods for bilevel optimization—0
Network Utility Maximization with Unknown Utility Functions: A Distributed, Data-Driven Bilevel Optimization Approach—0
On Finding Small Hyper-Gradients in Bilevel Optimization: Hardness Results and Improved Analysis—0
MAP: Towards Balanced Generalization of IID and OOD through Model-Agnostic AdaptersCode0
On Implicit Bias in Overparameterized Bilevel Optimization—0
Saliency-Augmented Memory Completion for Continual LearningCode0
Asynchronous Distributed Bilevel OptimizationCode0
Selective classification using a robust meta-learning approach—0
CPMLHO:Hyperparameter Tuning via Cutting Plane and Mixed-Level Optimization—0
DIAMOND: Taming Sample and Communication Complexities in Decentralized 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