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 151–175 of 423 papers

TitleStatusHype
A unified algorithm framework for mean-variance optimization in discounted Markov decision processes—0
A Gradient Method for Multilevel Optimization—0
A Data-Driven Sensor Placement Approach for Detecting Voltage Violations in Distribution Systems—0
Convexifying Regulation Market Clearing of State-of-Charge Dependent Bid—0
A Two-Timescale Framework for Bilevel Optimization: Complexity Analysis and Application to Actor-Critic—0
Convergent Reinforcement Learning with Function Approximation: A Bilevel Optimization Perspective—0
Convergence Properties of Stochastic Hypergradients—0
A Gradient-based Bilevel Optimization Approach for Tuning Hyperparameters in Machine Learning—0
Convergence and Sample Complexity of SGD in GANs—0
Contextual Stochastic Bilevel Optimization—0
A stochastic gradient method for trilevel optimization—0
Consistency analysis of bilevel data-driven learning in inverse problems—0
Conformal Predictive Programming for Chance Constrained Optimization—0
A Stackelberg game for incentive-based demand response in energy markets—0
A Globally Convergent Gradient-based Bilevel Hyperparameter Optimization Method—0
AdaSTE: An Adaptive Straight-Through Estimator to Train Binary Neural Networks—0
Achieving O(ε^-1.5) Complexity in Hessian/Jacobian-free Stochastic Bilevel Optimization—0
Concurrent Learning of Policy and Unknown Safety Constraints in Reinforcement Learning—0
Communication-Efficient Robust Federated Learning with Noisy Labels—0
A Single-Timescale Method for Stochastic Bilevel Optimization—0
Communication-Efficient Federated Bilevel Optimization with Local and Global Lower Level Problems—0
Communication-Efficient Federated Hypergradient Computation via Aggregated Iterative Differentiation—0
A Single-Loop Algorithm for Decentralized Bilevel Optimization—0
Age of Information Optimization in a RIS-Assisted Wireless Network—0
Combining Physics and Machine Learning for Network Flow Estimation—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