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 251–275 of 423 papers

TitleStatusHype
Solving Bilevel Optimal Bidding Problems Using Deep Convolutional Neural Networks—0
Online Bilevel Optimization: Regret Analysis of Online Alternating Gradient MethodsCode0
On the Convergence of Distributed Stochastic Bilevel Optimization Algorithms over a Network—0
Meta-Wrapper: Differentiable Wrapping Operator for User Interest Selection in CTR Prediction—0
Decentralized Gossip-Based Stochastic Bilevel Optimization over Communication Networks—0
Descent Steps of a Relation-Aware Energy Produce Heterogeneous Graph Neural NetworksCode0
A Conditional Gradient-based Method for Simple Bilevel Optimization with Convex Lower-level ProblemCode0
Communication-Efficient Robust Federated Learning with Noisy Labels—0
Towards Understanding Graph Neural Networks: An Algorithm Unrolling Perspective—0
Multi-block Min-max Bilevel Optimization with Applications in Multi-task Deep AUC Maximization—0
Algorithmic Foundations of Empirical X-risk Minimization—0
Will Bilevel Optimizers Benefit from Loops—0
Towards Extremely Fast Bilevel Optimization with Self-governed Convergence Guarantees—0
Set-based Meta-Interpolation for Few-Task Meta-Learning—0
PoisonedEncoder: Poisoning the Unlabeled Pre-training Data in Contrastive Learning—0
GPN: A Joint Structural Learning Framework for Graph Neural Networks—0
Beyond backpropagation: bilevel optimization through implicit differentiation and equilibrium propagation—0
Meta-learning Adaptive Deep Kernel Gaussian Processes for Molecular Property PredictionCode1
Second-Order Sensitivity Analysis for Bilevel OptimizationCode0
Local Stochastic Bilevel Optimization with Momentum-Based Variance Reduction—0
On the Convergence of Momentum-Based Algorithms for Federated Bilevel Optimization Problems—0
Handling Imbalanced Classification Problems With Support Vector Machines via Evolutionary Bilevel Optimization—0
A Stackelberg game for incentive-based demand response in energy markets—0
Single-level Adversarial Data Synthesis based on Neural Tangent KernelsCode1
A Learnable Variational Model for Joint Multimodal MRI Reconstruction and Synthesis—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