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 326–350 of 423 papers

TitleStatusHype
Inducing Equilibria via Incentives: Simultaneous Design-and-Play Ensures Global Convergence—0
An Optimization-Based Meta-Learning Model for MRI Reconstruction with Diverse Dataset—0
Inexact bilevel stochastic gradient methods for constrained and unconstrained lower-level problemsCode0
Towards Gradient-based Bilevel Optimization with Non-convex Followers and BeyondCode0
ES-Based Jacobian Enables Faster Bilevel Optimization—0
Programmatic Reinforcement Learning without Oracles—0
Learning Sample Reweighting for Adversarial Robustness—0
Discrepancy-Optimal Meta-Learning for Domain Generalization—0
Delve into the Performance Degradation of Differentiable Architecture Search—0
Data Summarization via Bilevel Optimization—0
Sign-MAML: Efficient Model-Agnostic Meta-Learning by SignSGDCode0
Integrating process design and control using reinforcement learning—0
Bilevel Optimization for Machine Learning: Algorithm Design and Convergence Analysis—0
Enhanced Bilevel Optimization via Bregman Distance—0
Tighter Analysis of Alternating Stochastic Gradient Method for Stochastic Nested Problems—0
DARTS-PRIME: Regularization and Scheduling Improve Constrained Optimization in Differentiable NAS—0
BiAdam: Fast Adaptive Bilevel Optimization Methods—0
Towards Adversarial Robustness via Transductive Learning—0
Fair Machine Learning under Limited Demographically Labeled DataCode0
Learning to Learn Semantic Factors in Heterogeneous Image Classification—0
A Gradient Method for Multilevel Optimization—0
Regularization Can Help Mitigate Poisoning Attacks... with the Right Hyperparameters—0
Graph Sanitation with Application to Node Classification—0
Bilevel Programs Meet Deep Learning: A Unifying View on Inference Learning Methods—0
Randomized Stochastic Variance-Reduced Methods for Multi-Task Stochastic 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